Instructions to use crumb/44m-init with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crumb/44m-init with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="crumb/44m-init", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("crumb/44m-init", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use crumb/44m-init with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "crumb/44m-init" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "crumb/44m-init", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/crumb/44m-init
- SGLang
How to use crumb/44m-init with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "crumb/44m-init" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "crumb/44m-init", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "crumb/44m-init" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "crumb/44m-init", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use crumb/44m-init with Docker Model Runner:
docker model run hf.co/crumb/44m-init
Download config.json from crumb/44m-init: direct link, hf CLI and curl.
- Browser
- Download file 935 Bytes
-
https://huggingface.co/crumb/44m-init/resolve/main/config.json
- Command line
-
hf download hf://crumb/44m-init/config.json
-
curl -L -o config.json https://huggingface.co/crumb/44m-init/resolve/main/config.json
935 Bytes
| { | |
| "activation_function": "gelu_new", | |
| "architectures": [ | |
| "GPT2ALMHeadModel" | |
| ], | |
| "attn_bias": false, | |
| "attn_pdrop": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_gpt2a.GPT2AConfig", | |
| "AutoModelForCausalLM": "modeling_gpt2a.GPT2ALMHeadModel" | |
| }, | |
| "bos_token_id": 50256, | |
| "embd_pdrop": 0.0, | |
| "eos_token_id": 50256, | |
| "initializer_range": 0.02, | |
| "layer_norm_epsilon": 1e-06, | |
| "mlp_bias": false, | |
| "model_type": "gpt2a", | |
| "n_embd": 640, | |
| "n_head": 8, | |
| "n_inner": 3072, | |
| "n_layer": 8, | |
| "n_positions": 4096, | |
| "reorder_and_upcast_attn": false, | |
| "resid_pdrop": 0.0, | |
| "scale_attn_by_inverse_layer_idx": false, | |
| "scale_attn_weights": true, | |
| "summary_activation": null, | |
| "summary_first_dropout": 0.1, | |
| "summary_proj_to_labels": true, | |
| "summary_type": "cls_index", | |
| "summary_use_proj": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.34.0.dev0", | |
| "use_cache": true, | |
| "vocab_size": 32000 | |
| } | |