model-metadata/hf_jobs_url · Datasets at Hugging Face

MiniMaxAI/MiniMax-M2.1

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"MiniMaxAI/MiniMax-M2.1\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('MiniMaxAI_MiniMax-M2.1_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in MiniMaxAI_MiniMax-M2.1_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/MiniMaxAI_MiniMax-M2.1_0.txt|MiniMaxAI_MiniMax-M2.1_0.txt>',\n )\n\n with open('MiniMaxAI_MiniMax-M2.1_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"MiniMaxAI/MiniMax-M2.1\", trust_remote_code=True)\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='MiniMaxAI_MiniMax-M2.1_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='MiniMaxAI_MiniMax-M2.1_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"MiniMaxAI/MiniMax-M2.1\", trust_remote_code=True, dtype=\"auto\")\n with open('MiniMaxAI_MiniMax-M2.1_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in MiniMaxAI_MiniMax-M2.1_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/MiniMaxAI_MiniMax-M2.1_1.txt|MiniMaxAI_MiniMax-M2.1_1.txt>',\n )\n\n with open('MiniMaxAI_MiniMax-M2.1_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoModelForCausalLM\nmodel = AutoModelForCausalLM.from_pretrained(\"MiniMaxAI/MiniMax-M2.1\", trust_remote_code=True, dtype=\"auto\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='MiniMaxAI_MiniMax-M2.1_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='MiniMaxAI_MiniMax-M2.1_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/MiniMaxAI_MiniMax-M2.1_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/MiniMaxAI_MiniMax-M2.1_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/MiniMaxAI_MiniMax-M2.1_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/MiniMaxAI_MiniMax-M2.1_1.txt" ]

1,107.58

Qwen/Qwen-Image-2512

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-2512\", dtype=torch.bfloat16, device_map=\"cuda\")\n \n prompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\n image = pipe(prompt).images[0]\n with open('Qwen_Qwen-Image-2512_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Qwen_Qwen-Image-2512_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Qwen_Qwen-Image-2512_0.txt|Qwen_Qwen-Image-2512_0.txt>',\n )\n\n with open('Qwen_Qwen-Image-2512_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-2512\", dtype=torch.bfloat16, device_map=\"cuda\")\n\nprompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\nimage = pipe(prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Qwen_Qwen-Image-2512_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Qwen_Qwen-Image-2512_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/Qwen_Qwen-Image-2512_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/Qwen_Qwen-Image-2512_0.txt" ]

0

LiquidAI/LFM2-2.6B-Exp

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"LiquidAI/LFM2-2.6B-Exp\")\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('LiquidAI_LFM2-2.6B-Exp_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in LiquidAI_LFM2-2.6B-Exp_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/LiquidAI_LFM2-2.6B-Exp_0.txt|LiquidAI_LFM2-2.6B-Exp_0.txt>',\n )\n\n with open('LiquidAI_LFM2-2.6B-Exp_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"LiquidAI/LFM2-2.6B-Exp\")\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='LiquidAI_LFM2-2.6B-Exp_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='LiquidAI_LFM2-2.6B-Exp_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"LiquidAI/LFM2-2.6B-Exp\")\n model = AutoModelForCausalLM.from_pretrained(\"LiquidAI/LFM2-2.6B-Exp\")\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n inputs = tokenizer.apply_chat_template(\n \tmessages,\n \tadd_generation_prompt=True,\n \ttokenize=True,\n \treturn_dict=True,\n \treturn_tensors=\"pt\",\n ).to(model.device)\n \n outputs = model.generate(**inputs, max_new_tokens=40)\n print(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n with open('LiquidAI_LFM2-2.6B-Exp_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in LiquidAI_LFM2-2.6B-Exp_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/LiquidAI_LFM2-2.6B-Exp_1.txt|LiquidAI_LFM2-2.6B-Exp_1.txt>',\n )\n\n with open('LiquidAI_LFM2-2.6B-Exp_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoTokenizer, AutoModelForCausalLM\n\ntokenizer = AutoTokenizer.from_pretrained(\"LiquidAI/LFM2-2.6B-Exp\")\nmodel = AutoModelForCausalLM.from_pretrained(\"LiquidAI/LFM2-2.6B-Exp\")\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\ninputs = tokenizer.apply_chat_template(\n\tmessages,\n\tadd_generation_prompt=True,\n\ttokenize=True,\n\treturn_dict=True,\n\treturn_tensors=\"pt\",\n).to(model.device)\n\noutputs = model.generate(**inputs, max_new_tokens=40)\nprint(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='LiquidAI_LFM2-2.6B-Exp_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='LiquidAI_LFM2-2.6B-Exp_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/LiquidAI_LFM2-2.6B-Exp_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/LiquidAI_LFM2-2.6B-Exp_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/LiquidAI_LFM2-2.6B-Exp_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/LiquidAI_LFM2-2.6B-Exp_1.txt" ]

6.22

tencent/WeDLM-8B-Instruct

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"tencent/WeDLM-8B-Instruct\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('tencent_WeDLM-8B-Instruct_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in tencent_WeDLM-8B-Instruct_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/tencent_WeDLM-8B-Instruct_0.txt|tencent_WeDLM-8B-Instruct_0.txt>',\n )\n\n with open('tencent_WeDLM-8B-Instruct_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"tencent/WeDLM-8B-Instruct\", trust_remote_code=True)\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='tencent_WeDLM-8B-Instruct_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='tencent_WeDLM-8B-Instruct_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"tencent/WeDLM-8B-Instruct\", trust_remote_code=True, dtype=\"auto\")\n with open('tencent_WeDLM-8B-Instruct_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in tencent_WeDLM-8B-Instruct_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/tencent_WeDLM-8B-Instruct_1.txt|tencent_WeDLM-8B-Instruct_1.txt>',\n )\n\n with open('tencent_WeDLM-8B-Instruct_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoModelForCausalLM\nmodel = AutoModelForCausalLM.from_pretrained(\"tencent/WeDLM-8B-Instruct\", trust_remote_code=True, dtype=\"auto\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='tencent_WeDLM-8B-Instruct_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='tencent_WeDLM-8B-Instruct_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/tencent_WeDLM-8B-Instruct_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/tencent_WeDLM-8B-Instruct_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/tencent_WeDLM-8B-Instruct_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/tencent_WeDLM-8B-Instruct_1.txt" ]

19.83

Qwen/Qwen-Image-Edit-2511

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n from diffusers.utils import load_image\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-Edit-2511\", dtype=torch.bfloat16, device_map=\"cuda\")\n \n prompt = \"Turn this cat into a dog\"\n input_image = load_image(\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png\")\n \n image = pipe(image=input_image, prompt=prompt).images[0]\n with open('Qwen_Qwen-Image-Edit-2511_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Qwen_Qwen-Image-Edit-2511_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Qwen_Qwen-Image-Edit-2511_0.txt|Qwen_Qwen-Image-Edit-2511_0.txt>',\n )\n\n with open('Qwen_Qwen-Image-Edit-2511_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\nfrom diffusers.utils import load_image\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-Edit-2511\", dtype=torch.bfloat16, device_map=\"cuda\")\n\nprompt = \"Turn this cat into a dog\"\ninput_image = load_image(\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png\")\n\nimage = pipe(image=input_image, prompt=prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Qwen_Qwen-Image-Edit-2511_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Qwen_Qwen-Image-Edit-2511_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/Qwen_Qwen-Image-Edit-2511_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/Qwen_Qwen-Image-Edit-2511_0.txt" ]

0

lilylilith/AnyPose

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n from diffusers.utils import load_image\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-Edit-2511\", dtype=torch.bfloat16, device_map=\"cuda\")\n pipe.load_lora_weights(\"lilylilith/AnyPose\")\n \n prompt = \"Turn this cat into a dog\"\n input_image = load_image(\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png\")\n \n image = pipe(image=input_image, prompt=prompt).images[0]\n with open('lilylilith_AnyPose_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in lilylilith_AnyPose_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/lilylilith_AnyPose_0.txt|lilylilith_AnyPose_0.txt>',\n )\n\n with open('lilylilith_AnyPose_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\nfrom diffusers.utils import load_image\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-Edit-2511\", dtype=torch.bfloat16, device_map=\"cuda\")\npipe.load_lora_weights(\"lilylilith/AnyPose\")\n\nprompt = \"Turn this cat into a dog\"\ninput_image = load_image(\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png\")\n\nimage = pipe(image=input_image, prompt=prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='lilylilith_AnyPose_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='lilylilith_AnyPose_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/lilylilith_AnyPose_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/lilylilith_AnyPose_0.txt" ]

0

LGAI-EXAONE/K-EXAONE-236B-A23B

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"LGAI-EXAONE/K-EXAONE-236B-A23B\")\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('LGAI-EXAONE_K-EXAONE-236B-A23B_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in LGAI-EXAONE_K-EXAONE-236B-A23B_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/LGAI-EXAONE_K-EXAONE-236B-A23B_0.txt|LGAI-EXAONE_K-EXAONE-236B-A23B_0.txt>',\n )\n\n with open('LGAI-EXAONE_K-EXAONE-236B-A23B_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"LGAI-EXAONE/K-EXAONE-236B-A23B\")\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='LGAI-EXAONE_K-EXAONE-236B-A23B_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='LGAI-EXAONE_K-EXAONE-236B-A23B_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"LGAI-EXAONE/K-EXAONE-236B-A23B\", dtype=\"auto\")\n with open('LGAI-EXAONE_K-EXAONE-236B-A23B_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in LGAI-EXAONE_K-EXAONE-236B-A23B_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/LGAI-EXAONE_K-EXAONE-236B-A23B_1.txt|LGAI-EXAONE_K-EXAONE-236B-A23B_1.txt>',\n )\n\n with open('LGAI-EXAONE_K-EXAONE-236B-A23B_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoModelForCausalLM\nmodel = AutoModelForCausalLM.from_pretrained(\"LGAI-EXAONE/K-EXAONE-236B-A23B\", dtype=\"auto\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='LGAI-EXAONE_K-EXAONE-236B-A23B_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='LGAI-EXAONE_K-EXAONE-236B-A23B_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/LGAI-EXAONE_K-EXAONE-236B-A23B_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/LGAI-EXAONE_K-EXAONE-236B-A23B_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/LGAI-EXAONE_K-EXAONE-236B-A23B_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/LGAI-EXAONE_K-EXAONE-236B-A23B_1.txt" ]

1,148.24

Qwen/Qwen-Image-Layered

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-Layered\", dtype=torch.bfloat16, device_map=\"cuda\")\n \n prompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\n image = pipe(prompt).images[0]\n with open('Qwen_Qwen-Image-Layered_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Qwen_Qwen-Image-Layered_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Qwen_Qwen-Image-Layered_0.txt|Qwen_Qwen-Image-Layered_0.txt>',\n )\n\n with open('Qwen_Qwen-Image-Layered_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-Layered\", dtype=torch.bfloat16, device_map=\"cuda\")\n\nprompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\nimage = pipe(prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Qwen_Qwen-Image-Layered_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Qwen_Qwen-Image-Layered_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/Qwen_Qwen-Image-Layered_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/Qwen_Qwen-Image-Layered_0.txt" ]

0

tencent/HY-Motion-1.0

[]

0

google/functiongemma-270m-it

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n from huggingface_hub import login\n login(new_session=False)\n with open('google_functiongemma-270m-it_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in google_functiongemma-270m-it_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/google_functiongemma-270m-it_0.txt|google_functiongemma-270m-it_0.txt>',\n )\n\n with open('google_functiongemma-270m-it_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nfrom huggingface_hub import login\nlogin(new_session=False)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='google_functiongemma-270m-it_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='google_functiongemma-270m-it_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"google/functiongemma-270m-it\")\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('google_functiongemma-270m-it_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in google_functiongemma-270m-it_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/google_functiongemma-270m-it_1.txt|google_functiongemma-270m-it_1.txt>',\n )\n\n with open('google_functiongemma-270m-it_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"google/functiongemma-270m-it\")\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='google_functiongemma-270m-it_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='google_functiongemma-270m-it_1.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"google/functiongemma-270m-it\")\n model = AutoModelForCausalLM.from_pretrained(\"google/functiongemma-270m-it\")\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n inputs = tokenizer.apply_chat_template(\n \tmessages,\n \tadd_generation_prompt=True,\n \ttokenize=True,\n \treturn_dict=True,\n \treturn_tensors=\"pt\",\n ).to(model.device)\n \n outputs = model.generate(**inputs, max_new_tokens=40)\n print(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n with open('google_functiongemma-270m-it_2.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in google_functiongemma-270m-it_2.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/google_functiongemma-270m-it_2.txt|google_functiongemma-270m-it_2.txt>',\n )\n\n with open('google_functiongemma-270m-it_2.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoTokenizer, AutoModelForCausalLM\n\ntokenizer = AutoTokenizer.from_pretrained(\"google/functiongemma-270m-it\")\nmodel = AutoModelForCausalLM.from_pretrained(\"google/functiongemma-270m-it\")\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\ninputs = tokenizer.apply_chat_template(\n\tmessages,\n\tadd_generation_prompt=True,\n\ttokenize=True,\n\treturn_dict=True,\n\treturn_tensors=\"pt\",\n).to(model.device)\n\noutputs = model.generate(**inputs, max_new_tokens=40)\nprint(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='google_functiongemma-270m-it_2.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='google_functiongemma-270m-it_2.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/google_functiongemma-270m-it_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/google_functiongemma-270m-it_1.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/google_functiongemma-270m-it_2.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/google_functiongemma-270m-it_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/google_functiongemma-270m-it_1.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/google_functiongemma-270m-it_2.txt" ]

0.65

tencent/HY-MT1.5-1.8B

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"translation\", model=\"tencent/HY-MT1.5-1.8B\")\n with open('tencent_HY-MT1.5-1.8B_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in tencent_HY-MT1.5-1.8B_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/tencent_HY-MT1.5-1.8B_0.txt|tencent_HY-MT1.5-1.8B_0.txt>',\n )\n\n with open('tencent_HY-MT1.5-1.8B_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"translation\", model=\"tencent/HY-MT1.5-1.8B\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='tencent_HY-MT1.5-1.8B_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='tencent_HY-MT1.5-1.8B_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"tencent/HY-MT1.5-1.8B\")\n model = AutoModelForCausalLM.from_pretrained(\"tencent/HY-MT1.5-1.8B\")\n with open('tencent_HY-MT1.5-1.8B_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in tencent_HY-MT1.5-1.8B_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/tencent_HY-MT1.5-1.8B_1.txt|tencent_HY-MT1.5-1.8B_1.txt>',\n )\n\n with open('tencent_HY-MT1.5-1.8B_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoTokenizer, AutoModelForCausalLM\n\ntokenizer = AutoTokenizer.from_pretrained(\"tencent/HY-MT1.5-1.8B\")\nmodel = AutoModelForCausalLM.from_pretrained(\"tencent/HY-MT1.5-1.8B\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='tencent_HY-MT1.5-1.8B_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='tencent_HY-MT1.5-1.8B_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/tencent_HY-MT1.5-1.8B_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/tencent_HY-MT1.5-1.8B_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/tencent_HY-MT1.5-1.8B_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/tencent_HY-MT1.5-1.8B_1.txt" ]

4.94

lightx2v/Qwen-Image-Edit-2511-Lightning

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n from diffusers.utils import load_image\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-Edit-2511\", dtype=torch.bfloat16, device_map=\"cuda\")\n pipe.load_lora_weights(\"lightx2v/Qwen-Image-Edit-2511-Lightning\")\n \n prompt = \"Turn this cat into a dog\"\n input_image = load_image(\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png\")\n \n image = pipe(image=input_image, prompt=prompt).images[0]\n with open('lightx2v_Qwen-Image-Edit-2511-Lightning_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in lightx2v_Qwen-Image-Edit-2511-Lightning_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/lightx2v_Qwen-Image-Edit-2511-Lightning_0.txt|lightx2v_Qwen-Image-Edit-2511-Lightning_0.txt>',\n )\n\n with open('lightx2v_Qwen-Image-Edit-2511-Lightning_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\nfrom diffusers.utils import load_image\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-Edit-2511\", dtype=torch.bfloat16, device_map=\"cuda\")\npipe.load_lora_weights(\"lightx2v/Qwen-Image-Edit-2511-Lightning\")\n\nprompt = \"Turn this cat into a dog\"\ninput_image = load_image(\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png\")\n\nimage = pipe(image=input_image, prompt=prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='lightx2v_Qwen-Image-Edit-2511-Lightning_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='lightx2v_Qwen-Image-Edit-2511-Lightning_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/lightx2v_Qwen-Image-Edit-2511-Lightning_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/lightx2v_Qwen-Image-Edit-2511-Lightning_0.txt" ]

0

nvidia/NitroGen

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('nvidia_NitroGen_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in nvidia_NitroGen_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/nvidia_NitroGen_0.txt|nvidia_NitroGen_0.txt>',\n )\n\n with open('nvidia_NitroGen_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# ⚠️ Type of model/library unknown.\n \n# Feel free to open a Pull request \n# for integration of the huggingface model hub\n# into the corresponding library =)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='nvidia_NitroGen_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='nvidia_NitroGen_0.txt',\n repo_type='dataset',\n )\n" ]

[ "DO NOT EXECUTE" ]

[ "WAS NOT EXECUTED" ]

0

fal/FLUX.2-dev-Turbo

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"black-forest-labs/FLUX.2-dev\", dtype=torch.bfloat16, device_map=\"cuda\")\n pipe.load_lora_weights(\"fal/FLUX.2-dev-Turbo\")\n \n prompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\n image = pipe(prompt).images[0]\n with open('fal_FLUX.2-dev-Turbo_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in fal_FLUX.2-dev-Turbo_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/fal_FLUX.2-dev-Turbo_0.txt|fal_FLUX.2-dev-Turbo_0.txt>',\n )\n\n with open('fal_FLUX.2-dev-Turbo_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"black-forest-labs/FLUX.2-dev\", dtype=torch.bfloat16, device_map=\"cuda\")\npipe.load_lora_weights(\"fal/FLUX.2-dev-Turbo\")\n\nprompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\nimage = pipe(prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='fal_FLUX.2-dev-Turbo_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='fal_FLUX.2-dev-Turbo_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/fal_FLUX.2-dev-Turbo_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/fal_FLUX.2-dev-Turbo_0.txt" ]

0

zai-org/GLM-4.7

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"zai-org/GLM-4.7\")\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('zai-org_GLM-4.7_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in zai-org_GLM-4.7_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/zai-org_GLM-4.7_0.txt|zai-org_GLM-4.7_0.txt>',\n )\n\n with open('zai-org_GLM-4.7_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"zai-org/GLM-4.7\")\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='zai-org_GLM-4.7_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='zai-org_GLM-4.7_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"zai-org/GLM-4.7\")\n model = AutoModelForCausalLM.from_pretrained(\"zai-org/GLM-4.7\")\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n inputs = tokenizer.apply_chat_template(\n \tmessages,\n \tadd_generation_prompt=True,\n \ttokenize=True,\n \treturn_dict=True,\n \treturn_tensors=\"pt\",\n ).to(model.device)\n \n outputs = model.generate(**inputs, max_new_tokens=40)\n print(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n with open('zai-org_GLM-4.7_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in zai-org_GLM-4.7_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/zai-org_GLM-4.7_1.txt|zai-org_GLM-4.7_1.txt>',\n )\n\n with open('zai-org_GLM-4.7_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoTokenizer, AutoModelForCausalLM\n\ntokenizer = AutoTokenizer.from_pretrained(\"zai-org/GLM-4.7\")\nmodel = AutoModelForCausalLM.from_pretrained(\"zai-org/GLM-4.7\")\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\ninputs = tokenizer.apply_chat_template(\n\tmessages,\n\tadd_generation_prompt=True,\n\ttokenize=True,\n\treturn_dict=True,\n\treturn_tensors=\"pt\",\n).to(model.device)\n\noutputs = model.generate(**inputs, max_new_tokens=40)\nprint(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='zai-org_GLM-4.7_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='zai-org_GLM-4.7_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/zai-org_GLM-4.7_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/zai-org_GLM-4.7_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/zai-org_GLM-4.7_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/zai-org_GLM-4.7_1.txt" ]

867.69

inclusionAI/TwinFlow-Z-Image-Turbo

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"inclusionAI/TwinFlow-Z-Image-Turbo\", dtype=torch.bfloat16, device_map=\"cuda\")\n \n prompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\n image = pipe(prompt).images[0]\n with open('inclusionAI_TwinFlow-Z-Image-Turbo_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in inclusionAI_TwinFlow-Z-Image-Turbo_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/inclusionAI_TwinFlow-Z-Image-Turbo_0.txt|inclusionAI_TwinFlow-Z-Image-Turbo_0.txt>',\n )\n\n with open('inclusionAI_TwinFlow-Z-Image-Turbo_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"inclusionAI/TwinFlow-Z-Image-Turbo\", dtype=torch.bfloat16, device_map=\"cuda\")\n\nprompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\nimage = pipe(prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='inclusionAI_TwinFlow-Z-Image-Turbo_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='inclusionAI_TwinFlow-Z-Image-Turbo_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/inclusionAI_TwinFlow-Z-Image-Turbo_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/inclusionAI_TwinFlow-Z-Image-Turbo_0.txt" ]

0

allura-forge/Llama-3.3-8B-Instruct

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('allura-forge_Llama-3.3-8B-Instruct_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in allura-forge_Llama-3.3-8B-Instruct_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/allura-forge_Llama-3.3-8B-Instruct_0.txt|allura-forge_Llama-3.3-8B-Instruct_0.txt>',\n )\n\n with open('allura-forge_Llama-3.3-8B-Instruct_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# ⚠️ Type of model/library unknown.\n \n# Feel free to open a Pull request \n# for integration of the huggingface model hub\n# into the corresponding library =)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='allura-forge_Llama-3.3-8B-Instruct_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='allura-forge_Llama-3.3-8B-Instruct_0.txt',\n repo_type='dataset',\n )\n" ]

[ "DO NOT EXECUTE" ]

[ "WAS NOT EXECUTED" ]

19.44

ResembleAI/chatterbox-turbo

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('ResembleAI_chatterbox-turbo_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in ResembleAI_chatterbox-turbo_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/ResembleAI_chatterbox-turbo_0.txt|ResembleAI_chatterbox-turbo_0.txt>',\n )\n\n with open('ResembleAI_chatterbox-turbo_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# ⚠️ Type of model/library unknown.\n \n# Feel free to open a Pull request \n# for integration of the huggingface model hub\n# into the corresponding library =)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='ResembleAI_chatterbox-turbo_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='ResembleAI_chatterbox-turbo_0.txt',\n repo_type='dataset',\n )\n" ]

[ "DO NOT EXECUTE" ]

[ "WAS NOT EXECUTED" ]

0

FunAudioLLM/Fun-Audio-Chat-8B

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForSeq2SeqLM\n model = AutoModelForSeq2SeqLM.from_pretrained(\"FunAudioLLM/Fun-Audio-Chat-8B\", dtype=\"auto\")\n with open('FunAudioLLM_Fun-Audio-Chat-8B_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in FunAudioLLM_Fun-Audio-Chat-8B_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/FunAudioLLM_Fun-Audio-Chat-8B_0.txt|FunAudioLLM_Fun-Audio-Chat-8B_0.txt>',\n )\n\n with open('FunAudioLLM_Fun-Audio-Chat-8B_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoModelForSeq2SeqLM\nmodel = AutoModelForSeq2SeqLM.from_pretrained(\"FunAudioLLM/Fun-Audio-Chat-8B\", dtype=\"auto\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='FunAudioLLM_Fun-Audio-Chat-8B_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='FunAudioLLM_Fun-Audio-Chat-8B_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/FunAudioLLM_Fun-Audio-Chat-8B_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/FunAudioLLM_Fun-Audio-Chat-8B_0.txt" ]

22.89

microsoft/TRELLIS.2-4B

[]

0

ekwek/Soprano-80M

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-to-speech\", model=\"ekwek/Soprano-80M\")\n with open('ekwek_Soprano-80M_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in ekwek_Soprano-80M_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/ekwek_Soprano-80M_0.txt|ekwek_Soprano-80M_0.txt>',\n )\n\n with open('ekwek_Soprano-80M_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-to-speech\", model=\"ekwek/Soprano-80M\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='ekwek_Soprano-80M_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='ekwek_Soprano-80M_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"ekwek/Soprano-80M\")\n model = AutoModelForCausalLM.from_pretrained(\"ekwek/Soprano-80M\")\n with open('ekwek_Soprano-80M_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in ekwek_Soprano-80M_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/ekwek_Soprano-80M_1.txt|ekwek_Soprano-80M_1.txt>',\n )\n\n with open('ekwek_Soprano-80M_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoTokenizer, AutoModelForCausalLM\n\ntokenizer = AutoTokenizer.from_pretrained(\"ekwek/Soprano-80M\")\nmodel = AutoModelForCausalLM.from_pretrained(\"ekwek/Soprano-80M\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='ekwek_Soprano-80M_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='ekwek_Soprano-80M_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/ekwek_Soprano-80M_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/ekwek_Soprano-80M_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/ekwek_Soprano-80M_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/ekwek_Soprano-80M_1.txt" ]

0.19

naver-hyperclovax/HyperCLOVAX-SEED-Think-32B

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"naver-hyperclovax/HyperCLOVAX-SEED-Think-32B\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_0.txt|naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_0.txt>',\n )\n\n with open('naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"naver-hyperclovax/HyperCLOVAX-SEED-Think-32B\", trust_remote_code=True)\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"naver-hyperclovax/HyperCLOVAX-SEED-Think-32B\", trust_remote_code=True, dtype=\"auto\")\n with open('naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_1.txt|naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_1.txt>',\n )\n\n with open('naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoModelForCausalLM\nmodel = AutoModelForCausalLM.from_pretrained(\"naver-hyperclovax/HyperCLOVAX-SEED-Think-32B\", trust_remote_code=True, dtype=\"auto\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/naver-hyperclovax_HyperCLOVAX-SEED-Think-32B_1.txt" ]

80.67

XiaomiMiMo/MiMo-V2-Flash

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"XiaomiMiMo/MiMo-V2-Flash\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('XiaomiMiMo_MiMo-V2-Flash_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in XiaomiMiMo_MiMo-V2-Flash_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/XiaomiMiMo_MiMo-V2-Flash_0.txt|XiaomiMiMo_MiMo-V2-Flash_0.txt>',\n )\n\n with open('XiaomiMiMo_MiMo-V2-Flash_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"XiaomiMiMo/MiMo-V2-Flash\", trust_remote_code=True)\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='XiaomiMiMo_MiMo-V2-Flash_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='XiaomiMiMo_MiMo-V2-Flash_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"XiaomiMiMo/MiMo-V2-Flash\", trust_remote_code=True, dtype=\"auto\")\n with open('XiaomiMiMo_MiMo-V2-Flash_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in XiaomiMiMo_MiMo-V2-Flash_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/XiaomiMiMo_MiMo-V2-Flash_1.txt|XiaomiMiMo_MiMo-V2-Flash_1.txt>',\n )\n\n with open('XiaomiMiMo_MiMo-V2-Flash_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoModelForCausalLM\nmodel = AutoModelForCausalLM.from_pretrained(\"XiaomiMiMo/MiMo-V2-Flash\", trust_remote_code=True, dtype=\"auto\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='XiaomiMiMo_MiMo-V2-Flash_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='XiaomiMiMo_MiMo-V2-Flash_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/XiaomiMiMo_MiMo-V2-Flash_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/XiaomiMiMo_MiMo-V2-Flash_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/XiaomiMiMo_MiMo-V2-Flash_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/XiaomiMiMo_MiMo-V2-Flash_1.txt" ]

1,500.25

nunchaku-tech/nunchaku-z-image-turbo

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"nunchaku-tech/nunchaku-z-image-turbo\", dtype=torch.bfloat16, device_map=\"cuda\")\n \n prompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\n image = pipe(prompt).images[0]\n with open('nunchaku-tech_nunchaku-z-image-turbo_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in nunchaku-tech_nunchaku-z-image-turbo_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/nunchaku-tech_nunchaku-z-image-turbo_0.txt|nunchaku-tech_nunchaku-z-image-turbo_0.txt>',\n )\n\n with open('nunchaku-tech_nunchaku-z-image-turbo_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"nunchaku-tech/nunchaku-z-image-turbo\", dtype=torch.bfloat16, device_map=\"cuda\")\n\nprompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\nimage = pipe(prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='nunchaku-tech_nunchaku-z-image-turbo_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='nunchaku-tech_nunchaku-z-image-turbo_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/nunchaku-tech_nunchaku-z-image-turbo_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/nunchaku-tech_nunchaku-z-image-turbo_0.txt" ]

0

Tongyi-MAI/Z-Image-Turbo

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"Tongyi-MAI/Z-Image-Turbo\", dtype=torch.bfloat16, device_map=\"cuda\")\n \n prompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\n image = pipe(prompt).images[0]\n with open('Tongyi-MAI_Z-Image-Turbo_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Tongyi-MAI_Z-Image-Turbo_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Tongyi-MAI_Z-Image-Turbo_0.txt|Tongyi-MAI_Z-Image-Turbo_0.txt>',\n )\n\n with open('Tongyi-MAI_Z-Image-Turbo_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"Tongyi-MAI/Z-Image-Turbo\", dtype=torch.bfloat16, device_map=\"cuda\")\n\nprompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\nimage = pipe(prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Tongyi-MAI_Z-Image-Turbo_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Tongyi-MAI_Z-Image-Turbo_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/Tongyi-MAI_Z-Image-Turbo_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/Tongyi-MAI_Z-Image-Turbo_0.txt" ]

0

TurboDiffusion/TurboWan2.2-I2V-A14B-720P

[]

0

YatharthS/MiraTTS

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('YatharthS_MiraTTS_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in YatharthS_MiraTTS_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/YatharthS_MiraTTS_0.txt|YatharthS_MiraTTS_0.txt>',\n )\n\n with open('YatharthS_MiraTTS_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# ⚠️ Type of model/library unknown.\n \n# Feel free to open a Pull request \n# for integration of the huggingface model hub\n# into the corresponding library =)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='YatharthS_MiraTTS_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='YatharthS_MiraTTS_0.txt',\n repo_type='dataset',\n )\n" ]

[ "DO NOT EXECUTE" ]

[ "WAS NOT EXECUTED" ]

1.23

upstage/Solar-Open-100B

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('upstage_Solar-Open-100B_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in upstage_Solar-Open-100B_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/upstage_Solar-Open-100B_0.txt|upstage_Solar-Open-100B_0.txt>',\n )\n\n with open('upstage_Solar-Open-100B_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# ⚠️ Type of model/library unknown.\n \n# Feel free to open a Pull request \n# for integration of the huggingface model hub\n# into the corresponding library =)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='upstage_Solar-Open-100B_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='upstage_Solar-Open-100B_0.txt',\n repo_type='dataset',\n )\n" ]

[ "DO NOT EXECUTE" ]

[ "WAS NOT EXECUTED" ]

248.57

naver-hyperclovax/HyperCLOVAX-SEED-Omni-8B

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"naver-hyperclovax/HyperCLOVAX-SEED-Omni-8B\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_0.txt|naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_0.txt>',\n )\n\n with open('naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"naver-hyperclovax/HyperCLOVAX-SEED-Omni-8B\", trust_remote_code=True)\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"naver-hyperclovax/HyperCLOVAX-SEED-Omni-8B\", trust_remote_code=True, dtype=\"auto\")\n with open('naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_1.txt|naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_1.txt>',\n )\n\n with open('naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoModelForCausalLM\nmodel = AutoModelForCausalLM.from_pretrained(\"naver-hyperclovax/HyperCLOVAX-SEED-Omni-8B\", trust_remote_code=True, dtype=\"auto\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/naver-hyperclovax_HyperCLOVAX-SEED-Omni-8B_1.txt" ]

52.02

skt/A.X-K1

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('skt_A.X-K1_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in skt_A.X-K1_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/skt_A.X-K1_0.txt|skt_A.X-K1_0.txt>',\n )\n\n with open('skt_A.X-K1_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# ⚠️ Type of model/library unknown.\n \n# Feel free to open a Pull request \n# for integration of the huggingface model hub\n# into the corresponding library =)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='skt_A.X-K1_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='skt_A.X-K1_0.txt',\n repo_type='dataset',\n )\n" ]

[ "DO NOT EXECUTE" ]

[ "WAS NOT EXECUTED" ]

1,256.69

black-forest-labs/FLUX.2-dev

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n from huggingface_hub import login\n login(new_session=False)\n with open('black-forest-labs_FLUX.2-dev_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in black-forest-labs_FLUX.2-dev_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/black-forest-labs_FLUX.2-dev_0.txt|black-forest-labs_FLUX.2-dev_0.txt>',\n )\n\n with open('black-forest-labs_FLUX.2-dev_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nfrom huggingface_hub import login\nlogin(new_session=False)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='black-forest-labs_FLUX.2-dev_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='black-forest-labs_FLUX.2-dev_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n from diffusers.utils import load_image\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"black-forest-labs/FLUX.2-dev\", dtype=torch.bfloat16, device_map=\"cuda\")\n \n prompt = \"Turn this cat into a dog\"\n input_image = load_image(\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png\")\n \n image = pipe(image=input_image, prompt=prompt).images[0]\n with open('black-forest-labs_FLUX.2-dev_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in black-forest-labs_FLUX.2-dev_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/black-forest-labs_FLUX.2-dev_1.txt|black-forest-labs_FLUX.2-dev_1.txt>',\n )\n\n with open('black-forest-labs_FLUX.2-dev_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\nfrom diffusers.utils import load_image\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"black-forest-labs/FLUX.2-dev\", dtype=torch.bfloat16, device_map=\"cuda\")\n\nprompt = \"Turn this cat into a dog\"\ninput_image = load_image(\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png\")\n\nimage = pipe(image=input_image, prompt=prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='black-forest-labs_FLUX.2-dev_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='black-forest-labs_FLUX.2-dev_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/black-forest-labs_FLUX.2-dev_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/black-forest-labs_FLUX.2-dev_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/black-forest-labs_FLUX.2-dev_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/black-forest-labs_FLUX.2-dev_1.txt" ]

0

facebook/sam3

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n from huggingface_hub import login\n login(new_session=False)\n with open('facebook_sam3_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in facebook_sam3_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/facebook_sam3_0.txt|facebook_sam3_0.txt>',\n )\n\n with open('facebook_sam3_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nfrom huggingface_hub import login\nlogin(new_session=False)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='facebook_sam3_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='facebook_sam3_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"mask-generation\", model=\"facebook/sam3\")\n with open('facebook_sam3_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in facebook_sam3_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/facebook_sam3_1.txt|facebook_sam3_1.txt>',\n )\n\n with open('facebook_sam3_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"mask-generation\", model=\"facebook/sam3\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='facebook_sam3_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='facebook_sam3_1.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoImageProcessor, AutoModel\n \n processor = AutoImageProcessor.from_pretrained(\"facebook/sam3\")\n model = AutoModel.from_pretrained(\"facebook/sam3\")\n with open('facebook_sam3_2.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in facebook_sam3_2.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/facebook_sam3_2.txt|facebook_sam3_2.txt>',\n )\n\n with open('facebook_sam3_2.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoImageProcessor, AutoModel\n\nprocessor = AutoImageProcessor.from_pretrained(\"facebook/sam3\")\nmodel = AutoModel.from_pretrained(\"facebook/sam3\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='facebook_sam3_2.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='facebook_sam3_2.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/facebook_sam3_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/facebook_sam3_1.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/facebook_sam3_2.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/facebook_sam3_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/facebook_sam3_1.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/facebook_sam3_2.txt" ]

4.16

Tongyi-MAI/MAI-UI-8B

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('Tongyi-MAI_MAI-UI-8B_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Tongyi-MAI_MAI-UI-8B_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Tongyi-MAI_MAI-UI-8B_0.txt|Tongyi-MAI_MAI-UI-8B_0.txt>',\n )\n\n with open('Tongyi-MAI_MAI-UI-8B_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# ⚠️ Type of model/library unknown.\n \n# Feel free to open a Pull request \n# for integration of the huggingface model hub\n# into the corresponding library =)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Tongyi-MAI_MAI-UI-8B_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Tongyi-MAI_MAI-UI-8B_0.txt',\n repo_type='dataset',\n )\n" ]

[ "DO NOT EXECUTE" ]

[ "WAS NOT EXECUTED" ]

21.23

google/t5gemma-2-270m-270m

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n from huggingface_hub import login\n login(new_session=False)\n with open('google_t5gemma-2-270m-270m_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in google_t5gemma-2-270m-270m_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/google_t5gemma-2-270m-270m_0.txt|google_t5gemma-2-270m-270m_0.txt>',\n )\n\n with open('google_t5gemma-2-270m-270m_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nfrom huggingface_hub import login\nlogin(new_session=False)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='google_t5gemma-2-270m-270m_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='google_t5gemma-2-270m-270m_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"image-text-to-text\", model=\"google/t5gemma-2-270m-270m\")\n with open('google_t5gemma-2-270m-270m_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in google_t5gemma-2-270m-270m_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/google_t5gemma-2-270m-270m_1.txt|google_t5gemma-2-270m-270m_1.txt>',\n )\n\n with open('google_t5gemma-2-270m-270m_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"image-text-to-text\", model=\"google/t5gemma-2-270m-270m\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='google_t5gemma-2-270m-270m_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='google_t5gemma-2-270m-270m_1.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoProcessor, AutoModelForSeq2SeqLM\n \n processor = AutoProcessor.from_pretrained(\"google/t5gemma-2-270m-270m\")\n model = AutoModelForSeq2SeqLM.from_pretrained(\"google/t5gemma-2-270m-270m\")\n with open('google_t5gemma-2-270m-270m_2.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in google_t5gemma-2-270m-270m_2.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/google_t5gemma-2-270m-270m_2.txt|google_t5gemma-2-270m-270m_2.txt>',\n )\n\n with open('google_t5gemma-2-270m-270m_2.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoProcessor, AutoModelForSeq2SeqLM\n\nprocessor = AutoProcessor.from_pretrained(\"google/t5gemma-2-270m-270m\")\nmodel = AutoModelForSeq2SeqLM.from_pretrained(\"google/t5gemma-2-270m-270m\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='google_t5gemma-2-270m-270m_2.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='google_t5gemma-2-270m-270m_2.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/google_t5gemma-2-270m-270m_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/google_t5gemma-2-270m-270m_1.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/google_t5gemma-2-270m-270m_2.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/google_t5gemma-2-270m-270m_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/google_t5gemma-2-270m-270m_1.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/google_t5gemma-2-270m-270m_2.txt" ]

1.9

alibaba-pai/Z-Image-Turbo-Fun-Controlnet-Union-2.1

[]

0

Maincode/Maincoder-1B

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"Maincode/Maincoder-1B\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('Maincode_Maincoder-1B_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Maincode_Maincoder-1B_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Maincode_Maincoder-1B_0.txt|Maincode_Maincoder-1B_0.txt>',\n )\n\n with open('Maincode_Maincoder-1B_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"Maincode/Maincoder-1B\", trust_remote_code=True)\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Maincode_Maincoder-1B_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Maincode_Maincoder-1B_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModel\n model = AutoModel.from_pretrained(\"Maincode/Maincoder-1B\", trust_remote_code=True, dtype=\"auto\")\n with open('Maincode_Maincoder-1B_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Maincode_Maincoder-1B_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Maincode_Maincoder-1B_1.txt|Maincode_Maincoder-1B_1.txt>',\n )\n\n with open('Maincode_Maincoder-1B_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoModel\nmodel = AutoModel.from_pretrained(\"Maincode/Maincoder-1B\", trust_remote_code=True, dtype=\"auto\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Maincode_Maincoder-1B_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Maincode_Maincoder-1B_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/Maincode_Maincoder-1B_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/Maincode_Maincoder-1B_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/Maincode_Maincoder-1B_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/Maincode_Maincoder-1B_1.txt" ]

2.48

apple/Sharp

[]

0

valiantcat/Qwen-Image-Edit-2511-Upscale2K

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n from diffusers.utils import load_image\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-Edit-2511\", dtype=torch.bfloat16, device_map=\"cuda\")\n pipe.load_lora_weights(\"valiantcat/Qwen-Image-Edit-2511-Upscale2K\")\n \n prompt = \"Upscale this picture to 4K resolution. \"\n input_image = load_image(\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png\")\n \n image = pipe(image=input_image, prompt=prompt).images[0]\n with open('valiantcat_Qwen-Image-Edit-2511-Upscale2K_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in valiantcat_Qwen-Image-Edit-2511-Upscale2K_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/valiantcat_Qwen-Image-Edit-2511-Upscale2K_0.txt|valiantcat_Qwen-Image-Edit-2511-Upscale2K_0.txt>',\n )\n\n with open('valiantcat_Qwen-Image-Edit-2511-Upscale2K_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\nfrom diffusers.utils import load_image\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-Edit-2511\", dtype=torch.bfloat16, device_map=\"cuda\")\npipe.load_lora_weights(\"valiantcat/Qwen-Image-Edit-2511-Upscale2K\")\n\nprompt = \"Upscale this picture to 4K resolution. \"\ninput_image = load_image(\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png\")\n\nimage = pipe(image=input_image, prompt=prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='valiantcat_Qwen-Image-Edit-2511-Upscale2K_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='valiantcat_Qwen-Image-Edit-2511-Upscale2K_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/valiantcat_Qwen-Image-Edit-2511-Upscale2K_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/valiantcat_Qwen-Image-Edit-2511-Upscale2K_0.txt" ]

0

facebook/sam-audio-large

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n from huggingface_hub import login\n login(new_session=False)\n with open('facebook_sam-audio-large_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in facebook_sam-audio-large_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/facebook_sam-audio-large_0.txt|facebook_sam-audio-large_0.txt>',\n )\n\n with open('facebook_sam-audio-large_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nfrom huggingface_hub import login\nlogin(new_session=False)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='facebook_sam-audio-large_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='facebook_sam-audio-large_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('facebook_sam-audio-large_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in facebook_sam-audio-large_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/facebook_sam-audio-large_1.txt|facebook_sam-audio-large_1.txt>',\n )\n\n with open('facebook_sam-audio-large_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# ⚠️ Type of model/library unknown.\n \n# Feel free to open a Pull request \n# for integration of the huggingface model hub\n# into the corresponding library =)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='facebook_sam-audio-large_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='facebook_sam-audio-large_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/facebook_sam-audio-large_0.py", "DO NOT EXECUTE" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/facebook_sam-audio-large_0.txt", "WAS NOT EXECUTED" ]

0

deepseek-ai/DeepSeek-V3.2

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"deepseek-ai/DeepSeek-V3.2\")\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('deepseek-ai_DeepSeek-V3.2_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in deepseek-ai_DeepSeek-V3.2_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/deepseek-ai_DeepSeek-V3.2_0.txt|deepseek-ai_DeepSeek-V3.2_0.txt>',\n )\n\n with open('deepseek-ai_DeepSeek-V3.2_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"deepseek-ai/DeepSeek-V3.2\")\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='deepseek-ai_DeepSeek-V3.2_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='deepseek-ai_DeepSeek-V3.2_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"deepseek-ai/DeepSeek-V3.2\", dtype=\"auto\")\n with open('deepseek-ai_DeepSeek-V3.2_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in deepseek-ai_DeepSeek-V3.2_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/deepseek-ai_DeepSeek-V3.2_1.txt|deepseek-ai_DeepSeek-V3.2_1.txt>',\n )\n\n with open('deepseek-ai_DeepSeek-V3.2_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoModelForCausalLM\nmodel = AutoModelForCausalLM.from_pretrained(\"deepseek-ai/DeepSeek-V3.2\", dtype=\"auto\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='deepseek-ai_DeepSeek-V3.2_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='deepseek-ai_DeepSeek-V3.2_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/deepseek-ai_DeepSeek-V3.2_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/deepseek-ai_DeepSeek-V3.2_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/deepseek-ai_DeepSeek-V3.2_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/deepseek-ai_DeepSeek-V3.2_1.txt" ]

1,659.65

Kevin-thu/StoryMem

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('Kevin-thu_StoryMem_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Kevin-thu_StoryMem_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Kevin-thu_StoryMem_0.txt|Kevin-thu_StoryMem_0.txt>',\n )\n\n with open('Kevin-thu_StoryMem_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# ⚠️ Type of model/library unknown.\n \n# Feel free to open a Pull request \n# for integration of the huggingface model hub\n# into the corresponding library =)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Kevin-thu_StoryMem_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Kevin-thu_StoryMem_0.txt',\n repo_type='dataset',\n )\n" ]

[ "DO NOT EXECUTE" ]

[ "WAS NOT EXECUTED" ]

0

Phr00t/Qwen-Image-Edit-Rapid-AIO

[]

0

Tongyi-Zhiwen/QwenLong-L1.5-30B-A3B

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('Tongyi-Zhiwen_QwenLong-L1.5-30B-A3B_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Tongyi-Zhiwen_QwenLong-L1.5-30B-A3B_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Tongyi-Zhiwen_QwenLong-L1.5-30B-A3B_0.txt|Tongyi-Zhiwen_QwenLong-L1.5-30B-A3B_0.txt>',\n )\n\n with open('Tongyi-Zhiwen_QwenLong-L1.5-30B-A3B_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# ⚠️ Type of model/library unknown.\n \n# Feel free to open a Pull request \n# for integration of the huggingface model hub\n# into the corresponding library =)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Tongyi-Zhiwen_QwenLong-L1.5-30B-A3B_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Tongyi-Zhiwen_QwenLong-L1.5-30B-A3B_0.txt',\n repo_type='dataset',\n )\n" ]

[ "DO NOT EXECUTE" ]

[ "WAS NOT EXECUTED" ]

73.93

Shakker-Labs/AWPortrait-Z

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"Tongyi-MAI/Z-Image-Turbo\", dtype=torch.bfloat16, device_map=\"cuda\")\n pipe.load_lora_weights(\"Shakker-Labs/AWPortrait-Z\")\n \n prompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\n image = pipe(prompt).images[0]\n with open('Shakker-Labs_AWPortrait-Z_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Shakker-Labs_AWPortrait-Z_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Shakker-Labs_AWPortrait-Z_0.txt|Shakker-Labs_AWPortrait-Z_0.txt>',\n )\n\n with open('Shakker-Labs_AWPortrait-Z_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"Tongyi-MAI/Z-Image-Turbo\", dtype=torch.bfloat16, device_map=\"cuda\")\npipe.load_lora_weights(\"Shakker-Labs/AWPortrait-Z\")\n\nprompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\nimage = pipe(prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Shakker-Labs_AWPortrait-Z_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Shakker-Labs_AWPortrait-Z_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/Shakker-Labs_AWPortrait-Z_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/Shakker-Labs_AWPortrait-Z_0.txt" ]

0

Nurburgring/BEYOND_REALITY_Z_IMAGE

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"Nurburgring/BEYOND_REALITY_Z_IMAGE\", dtype=torch.bfloat16, device_map=\"cuda\")\n \n prompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\n image = pipe(prompt).images[0]\n with open('Nurburgring_BEYOND_REALITY_Z_IMAGE_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Nurburgring_BEYOND_REALITY_Z_IMAGE_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Nurburgring_BEYOND_REALITY_Z_IMAGE_0.txt|Nurburgring_BEYOND_REALITY_Z_IMAGE_0.txt>',\n )\n\n with open('Nurburgring_BEYOND_REALITY_Z_IMAGE_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"Nurburgring/BEYOND_REALITY_Z_IMAGE\", dtype=torch.bfloat16, device_map=\"cuda\")\n\nprompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\nimage = pipe(prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Nurburgring_BEYOND_REALITY_Z_IMAGE_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Nurburgring_BEYOND_REALITY_Z_IMAGE_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/Nurburgring_BEYOND_REALITY_Z_IMAGE_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/Nurburgring_BEYOND_REALITY_Z_IMAGE_0.txt" ]

0

tencent/HY-MT1.5-7B

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"translation\", model=\"tencent/HY-MT1.5-7B\")\n with open('tencent_HY-MT1.5-7B_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in tencent_HY-MT1.5-7B_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/tencent_HY-MT1.5-7B_0.txt|tencent_HY-MT1.5-7B_0.txt>',\n )\n\n with open('tencent_HY-MT1.5-7B_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"translation\", model=\"tencent/HY-MT1.5-7B\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='tencent_HY-MT1.5-7B_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='tencent_HY-MT1.5-7B_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"tencent/HY-MT1.5-7B\")\n model = AutoModelForCausalLM.from_pretrained(\"tencent/HY-MT1.5-7B\")\n with open('tencent_HY-MT1.5-7B_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in tencent_HY-MT1.5-7B_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/tencent_HY-MT1.5-7B_1.txt|tencent_HY-MT1.5-7B_1.txt>',\n )\n\n with open('tencent_HY-MT1.5-7B_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoTokenizer, AutoModelForCausalLM\n\ntokenizer = AutoTokenizer.from_pretrained(\"tencent/HY-MT1.5-7B\")\nmodel = AutoModelForCausalLM.from_pretrained(\"tencent/HY-MT1.5-7B\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='tencent_HY-MT1.5-7B_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='tencent_HY-MT1.5-7B_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/tencent_HY-MT1.5-7B_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/tencent_HY-MT1.5-7B_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/tencent_HY-MT1.5-7B_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/tencent_HY-MT1.5-7B_1.txt" ]

19.44

zai-org/GLM-4.7-FP8

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"zai-org/GLM-4.7-FP8\")\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('zai-org_GLM-4.7-FP8_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in zai-org_GLM-4.7-FP8_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/zai-org_GLM-4.7-FP8_0.txt|zai-org_GLM-4.7-FP8_0.txt>',\n )\n\n with open('zai-org_GLM-4.7-FP8_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"zai-org/GLM-4.7-FP8\")\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='zai-org_GLM-4.7-FP8_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='zai-org_GLM-4.7-FP8_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"zai-org/GLM-4.7-FP8\")\n model = AutoModelForCausalLM.from_pretrained(\"zai-org/GLM-4.7-FP8\")\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n inputs = tokenizer.apply_chat_template(\n \tmessages,\n \tadd_generation_prompt=True,\n \ttokenize=True,\n \treturn_dict=True,\n \treturn_tensors=\"pt\",\n ).to(model.device)\n \n outputs = model.generate(**inputs, max_new_tokens=40)\n print(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n with open('zai-org_GLM-4.7-FP8_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in zai-org_GLM-4.7-FP8_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/zai-org_GLM-4.7-FP8_1.txt|zai-org_GLM-4.7-FP8_1.txt>',\n )\n\n with open('zai-org_GLM-4.7-FP8_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoTokenizer, AutoModelForCausalLM\n\ntokenizer = AutoTokenizer.from_pretrained(\"zai-org/GLM-4.7-FP8\")\nmodel = AutoModelForCausalLM.from_pretrained(\"zai-org/GLM-4.7-FP8\")\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\ninputs = tokenizer.apply_chat_template(\n\tmessages,\n\tadd_generation_prompt=True,\n\ttokenize=True,\n\treturn_dict=True,\n\treturn_tensors=\"pt\",\n).to(model.device)\n\noutputs = model.generate(**inputs, max_new_tokens=40)\nprint(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='zai-org_GLM-4.7-FP8_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='zai-org_GLM-4.7-FP8_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/zai-org_GLM-4.7-FP8_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/zai-org_GLM-4.7-FP8_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/zai-org_GLM-4.7-FP8_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/zai-org_GLM-4.7-FP8_1.txt" ]

1,735.97

lightx2v/Qwen-Image-2512-Lightning

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-2512\", dtype=torch.bfloat16, device_map=\"cuda\")\n pipe.load_lora_weights(\"lightx2v/Qwen-Image-2512-Lightning\")\n \n prompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\n image = pipe(prompt).images[0]\n with open('lightx2v_Qwen-Image-2512-Lightning_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in lightx2v_Qwen-Image-2512-Lightning_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/lightx2v_Qwen-Image-2512-Lightning_0.txt|lightx2v_Qwen-Image-2512-Lightning_0.txt>',\n )\n\n with open('lightx2v_Qwen-Image-2512-Lightning_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-2512\", dtype=torch.bfloat16, device_map=\"cuda\")\npipe.load_lora_weights(\"lightx2v/Qwen-Image-2512-Lightning\")\n\nprompt = \"Astronaut in a jungle, cold color palette, muted colors, detailed, 8k\"\nimage = pipe(prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='lightx2v_Qwen-Image-2512-Lightning_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='lightx2v_Qwen-Image-2512-Lightning_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/lightx2v_Qwen-Image-2512-Lightning_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/lightx2v_Qwen-Image-2512-Lightning_0.txt" ]

0

tencent/HY-WorldPlay

[]

0

tencent/Youtu-LLM-2B

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"tencent/Youtu-LLM-2B\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('tencent_Youtu-LLM-2B_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in tencent_Youtu-LLM-2B_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/tencent_Youtu-LLM-2B_0.txt|tencent_Youtu-LLM-2B_0.txt>',\n )\n\n with open('tencent_Youtu-LLM-2B_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"tencent/Youtu-LLM-2B\", trust_remote_code=True)\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='tencent_Youtu-LLM-2B_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='tencent_Youtu-LLM-2B_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"tencent/Youtu-LLM-2B\", trust_remote_code=True, dtype=\"auto\")\n with open('tencent_Youtu-LLM-2B_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in tencent_Youtu-LLM-2B_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/tencent_Youtu-LLM-2B_1.txt|tencent_Youtu-LLM-2B_1.txt>',\n )\n\n with open('tencent_Youtu-LLM-2B_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoModelForCausalLM\nmodel = AutoModelForCausalLM.from_pretrained(\"tencent/Youtu-LLM-2B\", trust_remote_code=True, dtype=\"auto\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='tencent_Youtu-LLM-2B_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='tencent_Youtu-LLM-2B_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/tencent_Youtu-LLM-2B_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/tencent_Youtu-LLM-2B_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/tencent_Youtu-LLM-2B_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/tencent_Youtu-LLM-2B_1.txt" ]

10.77

browser-use/bu-30b-a3b-preview

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"image-text-to-text\", model=\"browser-use/bu-30b-a3b-preview\")\n messages = [\n {\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"image\", \"url\": \"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG\"},\n {\"type\": \"text\", \"text\": \"What animal is on the candy?\"}\n ]\n },\n ]\n pipe(text=messages)\n with open('browser-use_bu-30b-a3b-preview_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in browser-use_bu-30b-a3b-preview_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/browser-use_bu-30b-a3b-preview_0.txt|browser-use_bu-30b-a3b-preview_0.txt>',\n )\n\n with open('browser-use_bu-30b-a3b-preview_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"image-text-to-text\", model=\"browser-use/bu-30b-a3b-preview\")\nmessages = [\n {\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"image\", \"url\": \"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG\"},\n {\"type\": \"text\", \"text\": \"What animal is on the candy?\"}\n ]\n },\n]\npipe(text=messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='browser-use_bu-30b-a3b-preview_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='browser-use_bu-30b-a3b-preview_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoProcessor, AutoModelForVision2Seq\n \n processor = AutoProcessor.from_pretrained(\"browser-use/bu-30b-a3b-preview\")\n model = AutoModelForVision2Seq.from_pretrained(\"browser-use/bu-30b-a3b-preview\")\n messages = [\n {\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"image\", \"url\": \"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG\"},\n {\"type\": \"text\", \"text\": \"What animal is on the candy?\"}\n ]\n },\n ]\n inputs = processor.apply_chat_template(\n \tmessages,\n \tadd_generation_prompt=True,\n \ttokenize=True,\n \treturn_dict=True,\n \treturn_tensors=\"pt\",\n ).to(model.device)\n \n outputs = model.generate(**inputs, max_new_tokens=40)\n print(processor.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n with open('browser-use_bu-30b-a3b-preview_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in browser-use_bu-30b-a3b-preview_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/browser-use_bu-30b-a3b-preview_1.txt|browser-use_bu-30b-a3b-preview_1.txt>',\n )\n\n with open('browser-use_bu-30b-a3b-preview_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoProcessor, AutoModelForVision2Seq\n\nprocessor = AutoProcessor.from_pretrained(\"browser-use/bu-30b-a3b-preview\")\nmodel = AutoModelForVision2Seq.from_pretrained(\"browser-use/bu-30b-a3b-preview\")\nmessages = [\n {\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"image\", \"url\": \"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG\"},\n {\"type\": \"text\", \"text\": \"What animal is on the candy?\"}\n ]\n },\n]\ninputs = processor.apply_chat_template(\n\tmessages,\n\tadd_generation_prompt=True,\n\ttokenize=True,\n\treturn_dict=True,\n\treturn_tensors=\"pt\",\n).to(model.device)\n\noutputs = model.generate(**inputs, max_new_tokens=40)\nprint(processor.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='browser-use_bu-30b-a3b-preview_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='browser-use_bu-30b-a3b-preview_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/browser-use_bu-30b-a3b-preview_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/browser-use_bu-30b-a3b-preview_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/browser-use_bu-30b-a3b-preview_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/browser-use_bu-30b-a3b-preview_1.txt" ]

75.24

stdstu123/Yume-5B-720P

[]

0

Qwen/Qwen-Image-Edit

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n import torch\n from diffusers import DiffusionPipeline\n from diffusers.utils import load_image\n \n # switch to \"mps\" for apple devices\n pipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-Edit\", dtype=torch.bfloat16, device_map=\"cuda\")\n \n prompt = \"Turn this cat into a dog\"\n input_image = load_image(\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png\")\n \n image = pipe(image=input_image, prompt=prompt).images[0]\n with open('Qwen_Qwen-Image-Edit_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Qwen_Qwen-Image-Edit_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Qwen_Qwen-Image-Edit_0.txt|Qwen_Qwen-Image-Edit_0.txt>',\n )\n\n with open('Qwen_Qwen-Image-Edit_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nimport torch\nfrom diffusers import DiffusionPipeline\nfrom diffusers.utils import load_image\n\n# switch to \"mps\" for apple devices\npipe = DiffusionPipeline.from_pretrained(\"Qwen/Qwen-Image-Edit\", dtype=torch.bfloat16, device_map=\"cuda\")\n\nprompt = \"Turn this cat into a dog\"\ninput_image = load_image(\"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png\")\n\nimage = pipe(image=input_image, prompt=prompt).images[0]\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Qwen_Qwen-Image-Edit_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Qwen_Qwen-Image-Edit_0.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/Qwen_Qwen-Image-Edit_0.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/Qwen_Qwen-Image-Edit_0.txt" ]

0

google/t5gemma-2-4b-4b

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n from huggingface_hub import login\n login(new_session=False)\n with open('google_t5gemma-2-4b-4b_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in google_t5gemma-2-4b-4b_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/google_t5gemma-2-4b-4b_0.txt|google_t5gemma-2-4b-4b_0.txt>',\n )\n\n with open('google_t5gemma-2-4b-4b_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \nfrom huggingface_hub import login\nlogin(new_session=False)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='google_t5gemma-2-4b-4b_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='google_t5gemma-2-4b-4b_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"image-text-to-text\", model=\"google/t5gemma-2-4b-4b\")\n with open('google_t5gemma-2-4b-4b_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in google_t5gemma-2-4b-4b_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/google_t5gemma-2-4b-4b_1.txt|google_t5gemma-2-4b-4b_1.txt>',\n )\n\n with open('google_t5gemma-2-4b-4b_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"image-text-to-text\", model=\"google/t5gemma-2-4b-4b\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='google_t5gemma-2-4b-4b_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='google_t5gemma-2-4b-4b_1.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoProcessor, AutoModelForSeq2SeqLM\n \n processor = AutoProcessor.from_pretrained(\"google/t5gemma-2-4b-4b\")\n model = AutoModelForSeq2SeqLM.from_pretrained(\"google/t5gemma-2-4b-4b\")\n with open('google_t5gemma-2-4b-4b_2.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in google_t5gemma-2-4b-4b_2.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/google_t5gemma-2-4b-4b_2.txt|google_t5gemma-2-4b-4b_2.txt>',\n )\n\n with open('google_t5gemma-2-4b-4b_2.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoProcessor, AutoModelForSeq2SeqLM\n\nprocessor = AutoProcessor.from_pretrained(\"google/t5gemma-2-4b-4b\")\nmodel = AutoModelForSeq2SeqLM.from_pretrained(\"google/t5gemma-2-4b-4b\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='google_t5gemma-2-4b-4b_2.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='google_t5gemma-2-4b-4b_2.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/google_t5gemma-2-4b-4b_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/google_t5gemma-2-4b-4b_1.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/google_t5gemma-2-4b-4b_2.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/google_t5gemma-2-4b-4b_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/google_t5gemma-2-4b-4b_1.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/google_t5gemma-2-4b-4b_2.txt" ]

21.43

YatharthS/FlashSR

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('YatharthS_FlashSR_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in YatharthS_FlashSR_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/YatharthS_FlashSR_0.txt|YatharthS_FlashSR_0.txt>',\n )\n\n with open('YatharthS_FlashSR_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# ⚠️ Type of model/library unknown.\n \n# Feel free to open a Pull request \n# for integration of the huggingface model hub\n# into the corresponding library =)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='YatharthS_FlashSR_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='YatharthS_FlashSR_0.txt',\n repo_type='dataset',\n )\n" ]

[ "DO NOT EXECUTE" ]

[ "WAS NOT EXECUTED" ]

0

FunAudioLLM/Fun-CosyVoice3-0.5B-2512

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('FunAudioLLM_Fun-CosyVoice3-0.5B-2512_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in FunAudioLLM_Fun-CosyVoice3-0.5B-2512_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/FunAudioLLM_Fun-CosyVoice3-0.5B-2512_0.txt|FunAudioLLM_Fun-CosyVoice3-0.5B-2512_0.txt>',\n )\n\n with open('FunAudioLLM_Fun-CosyVoice3-0.5B-2512_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# ⚠️ Type of model/library unknown.\n \n# Feel free to open a Pull request \n# for integration of the huggingface model hub\n# into the corresponding library =)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='FunAudioLLM_Fun-CosyVoice3-0.5B-2512_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='FunAudioLLM_Fun-CosyVoice3-0.5B-2512_0.txt',\n repo_type='dataset',\n )\n" ]

[ "DO NOT EXECUTE" ]

[ "WAS NOT EXECUTED" ]

0

Wuli-art/Qwen-Image-2512-Turbo-LoRA

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # ⚠️ Type of model/library unknown.\n \n # Feel free to open a Pull request \n # for integration of the huggingface model hub\n # into the corresponding library =)\n with open('Wuli-art_Qwen-Image-2512-Turbo-LoRA_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Wuli-art_Qwen-Image-2512-Turbo-LoRA_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Wuli-art_Qwen-Image-2512-Turbo-LoRA_0.txt|Wuli-art_Qwen-Image-2512-Turbo-LoRA_0.txt>',\n )\n\n with open('Wuli-art_Qwen-Image-2512-Turbo-LoRA_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# ⚠️ Type of model/library unknown.\n \n# Feel free to open a Pull request \n# for integration of the huggingface model hub\n# into the corresponding library =)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Wuli-art_Qwen-Image-2512-Turbo-LoRA_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Wuli-art_Qwen-Image-2512-Turbo-LoRA_0.txt',\n repo_type='dataset',\n )\n" ]

[ "DO NOT EXECUTE" ]

[ "WAS NOT EXECUTED" ]

0

Qwen/Qwen3-4B-Instruct-2507

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"Qwen/Qwen3-4B-Instruct-2507\")\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('Qwen_Qwen3-4B-Instruct-2507_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Qwen_Qwen3-4B-Instruct-2507_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Qwen_Qwen3-4B-Instruct-2507_0.txt|Qwen_Qwen3-4B-Instruct-2507_0.txt>',\n )\n\n with open('Qwen_Qwen3-4B-Instruct-2507_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"Qwen/Qwen3-4B-Instruct-2507\")\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Qwen_Qwen3-4B-Instruct-2507_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Qwen_Qwen3-4B-Instruct-2507_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"Qwen/Qwen3-4B-Instruct-2507\")\n model = AutoModelForCausalLM.from_pretrained(\"Qwen/Qwen3-4B-Instruct-2507\")\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n inputs = tokenizer.apply_chat_template(\n \tmessages,\n \tadd_generation_prompt=True,\n \ttokenize=True,\n \treturn_dict=True,\n \treturn_tensors=\"pt\",\n ).to(model.device)\n \n outputs = model.generate(**inputs, max_new_tokens=40)\n print(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n with open('Qwen_Qwen3-4B-Instruct-2507_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Qwen_Qwen3-4B-Instruct-2507_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Qwen_Qwen3-4B-Instruct-2507_1.txt|Qwen_Qwen3-4B-Instruct-2507_1.txt>',\n )\n\n with open('Qwen_Qwen3-4B-Instruct-2507_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoTokenizer, AutoModelForCausalLM\n\ntokenizer = AutoTokenizer.from_pretrained(\"Qwen/Qwen3-4B-Instruct-2507\")\nmodel = AutoModelForCausalLM.from_pretrained(\"Qwen/Qwen3-4B-Instruct-2507\")\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\ninputs = tokenizer.apply_chat_template(\n\tmessages,\n\tadd_generation_prompt=True,\n\ttokenize=True,\n\treturn_dict=True,\n\treturn_tensors=\"pt\",\n).to(model.device)\n\noutputs = model.generate(**inputs, max_new_tokens=40)\nprint(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Qwen_Qwen3-4B-Instruct-2507_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Qwen_Qwen3-4B-Instruct-2507_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/Qwen_Qwen3-4B-Instruct-2507_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/Qwen_Qwen3-4B-Instruct-2507_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/Qwen_Qwen3-4B-Instruct-2507_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/Qwen_Qwen3-4B-Instruct-2507_1.txt" ]

9.74

Kijai/WanVideo_comfy

[]

0

Comfy-Org/Qwen-Image-Edit_ComfyUI

[]

0

openai/gpt-oss-120b

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"openai/gpt-oss-120b\")\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('openai_gpt-oss-120b_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in openai_gpt-oss-120b_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/openai_gpt-oss-120b_0.txt|openai_gpt-oss-120b_0.txt>',\n )\n\n with open('openai_gpt-oss-120b_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"openai/gpt-oss-120b\")\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='openai_gpt-oss-120b_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='openai_gpt-oss-120b_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoTokenizer, AutoModelForCausalLM\n \n tokenizer = AutoTokenizer.from_pretrained(\"openai/gpt-oss-120b\")\n model = AutoModelForCausalLM.from_pretrained(\"openai/gpt-oss-120b\")\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n inputs = tokenizer.apply_chat_template(\n \tmessages,\n \tadd_generation_prompt=True,\n \ttokenize=True,\n \treturn_dict=True,\n \treturn_tensors=\"pt\",\n ).to(model.device)\n \n outputs = model.generate(**inputs, max_new_tokens=40)\n print(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n with open('openai_gpt-oss-120b_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in openai_gpt-oss-120b_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/openai_gpt-oss-120b_1.txt|openai_gpt-oss-120b_1.txt>',\n )\n\n with open('openai_gpt-oss-120b_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoTokenizer, AutoModelForCausalLM\n\ntokenizer = AutoTokenizer.from_pretrained(\"openai/gpt-oss-120b\")\nmodel = AutoModelForCausalLM.from_pretrained(\"openai/gpt-oss-120b\")\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\ninputs = tokenizer.apply_chat_template(\n\tmessages,\n\tadd_generation_prompt=True,\n\ttokenize=True,\n\treturn_dict=True,\n\treturn_tensors=\"pt\",\n).to(model.device)\n\noutputs = model.generate(**inputs, max_new_tokens=40)\nprint(tokenizer.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='openai_gpt-oss-120b_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='openai_gpt-oss-120b_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/openai_gpt-oss-120b_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/openai_gpt-oss-120b_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/openai_gpt-oss-120b_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/openai_gpt-oss-120b_1.txt" ]

291.57

Comfy-Org/z_image_turbo

[]

0

IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"text-generation\", model=\"IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct\", trust_remote_code=True)\n messages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n ]\n pipe(messages)\n with open('IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_0.txt|IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_0.txt>',\n )\n\n with open('IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"text-generation\", model=\"IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct\", trust_remote_code=True)\nmessages = [\n {\"role\": \"user\", \"content\": \"Who are you?\"},\n]\npipe(messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoModelForCausalLM\n model = AutoModelForCausalLM.from_pretrained(\"IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct\", trust_remote_code=True, dtype=\"auto\")\n with open('IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_1.txt|IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_1.txt>',\n )\n\n with open('IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoModelForCausalLM\nmodel = AutoModelForCausalLM.from_pretrained(\"IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct\", trust_remote_code=True, dtype=\"auto\")\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/IQuestLab_IQuest-Coder-V1-40B-Loop-Instruct_1.txt" ]

96.36

Qwen/Qwen3-VL-8B-Instruct

[ "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Use a pipeline as a high-level helper\n from transformers import pipeline\n \n pipe = pipeline(\"image-text-to-text\", model=\"Qwen/Qwen3-VL-8B-Instruct\")\n messages = [\n {\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"image\", \"url\": \"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG\"},\n {\"type\": \"text\", \"text\": \"What animal is on the candy?\"}\n ]\n },\n ]\n pipe(text=messages)\n with open('Qwen_Qwen3-VL-8B-Instruct_0.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Qwen_Qwen3-VL-8B-Instruct_0.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Qwen_Qwen3-VL-8B-Instruct_0.txt|Qwen_Qwen3-VL-8B-Instruct_0.txt>',\n )\n\n with open('Qwen_Qwen3-VL-8B-Instruct_0.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Use a pipeline as a high-level helper\nfrom transformers import pipeline\n\npipe = pipeline(\"image-text-to-text\", model=\"Qwen/Qwen3-VL-8B-Instruct\")\nmessages = [\n {\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"image\", \"url\": \"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG\"},\n {\"type\": \"text\", \"text\": \"What animal is on the candy?\"}\n ]\n },\n]\npipe(text=messages)\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Qwen_Qwen3-VL-8B-Instruct_0.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Qwen_Qwen3-VL-8B-Instruct_0.txt',\n repo_type='dataset',\n )\n", "# /// script\n# requires-python = \">=3.12\"\n# dependencies = [\n# \"numpy\",\n# \"einops\",\n# \"pandas\",\n# \"matplotlib\",\n# \"protobuf\",\n# \"torch\",\n# \"sentencepiece\",\n# \"torchvision\",\n# \"transformers\",\n# \"timm\",\n# \"diffusers\",\n# \"sentence-transformers\",\n# \"accelerate\",\n# \"peft\",\n# \"slack-sdk\",\n# ]\n# ///\n\ntry:\n # Load model directly\n from transformers import AutoProcessor, AutoModelForVision2Seq\n \n processor = AutoProcessor.from_pretrained(\"Qwen/Qwen3-VL-8B-Instruct\")\n model = AutoModelForVision2Seq.from_pretrained(\"Qwen/Qwen3-VL-8B-Instruct\")\n messages = [\n {\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"image\", \"url\": \"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG\"},\n {\"type\": \"text\", \"text\": \"What animal is on the candy?\"}\n ]\n },\n ]\n inputs = processor.apply_chat_template(\n \tmessages,\n \tadd_generation_prompt=True,\n \ttokenize=True,\n \treturn_dict=True,\n \treturn_tensors=\"pt\",\n ).to(model.device)\n \n outputs = model.generate(**inputs, max_new_tokens=40)\n print(processor.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n with open('Qwen_Qwen3-VL-8B-Instruct_1.txt', 'w', encoding='utf-8') as f:\n f.write('Everything was good in Qwen_Qwen3-VL-8B-Instruct_1.txt')\nexcept Exception as e:\n import os\n from slack_sdk import WebClient\n client = WebClient(token=os.environ['SLACK_TOKEN'])\n client.chat_postMessage(\n channel='#hub-model-metadata-snippets-sprint',\n text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Qwen_Qwen3-VL-8B-Instruct_1.txt|Qwen_Qwen3-VL-8B-Instruct_1.txt>',\n )\n\n with open('Qwen_Qwen3-VL-8B-Instruct_1.txt', 'a', encoding='utf-8') as f:\n import traceback\n f.write('''```CODE: \n# Load model directly\nfrom transformers import AutoProcessor, AutoModelForVision2Seq\n\nprocessor = AutoProcessor.from_pretrained(\"Qwen/Qwen3-VL-8B-Instruct\")\nmodel = AutoModelForVision2Seq.from_pretrained(\"Qwen/Qwen3-VL-8B-Instruct\")\nmessages = [\n {\n \"role\": \"user\",\n \"content\": [\n {\"type\": \"image\", \"url\": \"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG\"},\n {\"type\": \"text\", \"text\": \"What animal is on the candy?\"}\n ]\n },\n]\ninputs = processor.apply_chat_template(\n\tmessages,\n\tadd_generation_prompt=True,\n\ttokenize=True,\n\treturn_dict=True,\n\treturn_tensors=\"pt\",\n).to(model.device)\n\noutputs = model.generate(**inputs, max_new_tokens=40)\nprint(processor.decode(outputs[0][inputs[\"input_ids\"].shape[-1]:]))\n```\n\nERROR: \n''')\n traceback.print_exc(file=f)\n \nfinally:\n from huggingface_hub import upload_file\n upload_file(\n path_or_fileobj='Qwen_Qwen3-VL-8B-Instruct_1.txt',\n repo_id='model-metadata/code_execution_files',\n path_in_repo='Qwen_Qwen3-VL-8B-Instruct_1.txt',\n repo_type='dataset',\n )\n" ]

[ "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/Qwen_Qwen3-VL-8B-Instruct_0.py", "https://huggingface.co/datasets/model-metadata/code_python_files/raw/main/Qwen_Qwen3-VL-8B-Instruct_1.py" ]

[ "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/Qwen_Qwen3-VL-8B-Instruct_0.txt", "https://huggingface.co/datasets/model-metadata/code_execution_files/raw/main/Qwen_Qwen3-VL-8B-Instruct_1.txt" ]

21.23