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upvoted an article about 1 month ago
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Releasing the largest multilingual open pretraining dataset

By Pclanglais โ€ข
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reacted to pagezyhf's post with ๐Ÿ‘ about 1 month ago
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Hello Hugging Face Community,

I'd like to share here a bit more about our Deep Learning Containers (DLCs) we built with Google Cloud, to transform the way you build AI with open models on this platform!

With pre-configured, optimized environments for PyTorch Training (GPU) and Inference (CPU/GPU), Text Generation Inference (GPU), and Text Embeddings Inference (CPU/GPU), the Hugging Face DLCs offer:

โšก Optimized performance on Google Cloud's infrastructure, with TGI, TEI, and PyTorch acceleration.
๐Ÿ› ๏ธ Hassle-free environment setup, no more dependency issues.
๐Ÿ”„ Seamless updates to the latest stable versions.
๐Ÿ’ผ Streamlined workflow, reducing dev and maintenance overheads.
๐Ÿ”’ Robust security features of Google Cloud.
โ˜๏ธ Fine-tuned for optimal performance, integrated with GKE and Vertex AI.
๐Ÿ“ฆ Community examples for easy experimentation and implementation.
๐Ÿ”œ TPU support for PyTorch Training/Inference and Text Generation Inference is coming soon!

Find the documentation at https://huggingface.co/docs/google-cloud/en/index
If you need support, open a conversation on the forum: https://discuss.huggingface.co/c/google-cloud/69
reacted to not-lain's post with ๐Ÿ”ฅ about 1 month ago
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ever wondered how you can make an API call to a visual-question-answering model without sending an image url ๐Ÿ‘€

you can do that by converting your local image to base64 and sending it to the API.

recently I made some changes to my library "loadimg" that allows you to make converting images to base64 a breeze.
๐Ÿ”— https://github.com/not-lain/loadimg

API request example ๐Ÿ› ๏ธ:
from loadimg import load_img
from huggingface_hub import InferenceClient

# or load a local image
my_b64_img = load_img(imgPath_url_pillow_or_numpy ,output_type="base64" ) 

client = InferenceClient(api_key="hf_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")

messages = [
	{
		"role": "user",
		"content": [
			{
				"type": "text",
				"text": "Describe this image in one sentence."
			},
			{
				"type": "image_url",
				"image_url": {
					"url": my_b64_img # base64 allows using images without uploading them to the web
				}
			}
		]
	}
]

stream = client.chat.completions.create(
    model="meta-llama/Llama-3.2-11B-Vision-Instruct", 
	messages=messages, 
	max_tokens=500,
	stream=True
)

for chunk in stream:
    print(chunk.choices[0].delta.content, end="")
reacted to AdinaY's post with ๐Ÿ”ฅ about 1 month ago
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Letโ€™s dive into the exciting releases from the Chinese community last week ๐Ÿ”ฅ๐Ÿš€
More details ๐Ÿ‘‰ https://huggingface.co/zh-ai-community

Code model:
โœจQwen 2.5 coder by Alibaba Qwen
Qwen/qwen25-coder-66eaa22e6f99801bf65b0c2f
โœจOpenCoder by InflyAI - Fully open code model๐Ÿ™Œ
infly/opencoder-672cec44bbb86c39910fb55e

Image model:
โœจHunyuan3D-1.0 by Tencent
tencent/Hunyuan3D-1

MLLM:
โœจJanusFlow by DeepSeek
deepseek-ai/JanusFlow-1.3B
deepseek-ai/JanusFlow-1.3B
โœจMono-InternVL-2B by OpenGVlab
OpenGVLab/Mono-InternVL-2B

Video model:
โœจCogVideoX 1.5 by ChatGLM
THUDM/CogVideoX1.5-5B-SAT

Audio model:
โœจFish Agent by FishAudio
fishaudio/fish-agent-v0.1-3b

Dataset:
โœจOPI dataset by BAAIBeijing
BAAI/OPI
reacted to m-ric's post with ๐Ÿ”ฅ about 1 month ago
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๐—ง๐—ต๐—ฒ ๐—ป๐—ฒ๐˜…๐˜ ๐—ฏ๐—ถ๐—ด ๐˜€๐—ผ๐—ฐ๐—ถ๐—ฎ๐—น ๐—ป๐—ฒ๐˜๐˜„๐—ผ๐—ฟ๐—ธ ๐—ถ๐˜€ ๐—ป๐—ผ๐˜ ๐Ÿฆ‹, ๐—ถ๐˜'๐˜€ ๐—›๐˜‚๐—ฏ ๐—ฃ๐—ผ๐˜€๐˜๐˜€! [INSERT STONKS MEME WITH LASER EYES]

See below: I got 105k impressions since regularly posting Hub Posts, coming close to my 275k on Twitter!

โš™๏ธ Computed with the great dataset maxiw/hf-posts
โš™๏ธ Thanks to Qwen2.5-Coder-32B for showing me how to access dict attributes in a SQL request!

cc @merve who's far in front of me
ยท
reacted to merve's post with ๐Ÿ”ฅ about 1 month ago
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Amazing past days at open ML, it's raining coding models, let's have a recap ๐ŸŒง๏ธ Find all models and datasets here merve/nov-15-releases-67372d0ebdc354756a52ecd0

Models
๐Ÿ’ป Coding: Qwen team released two Qwen2.5-Coder checkpoints of 32B and 7B. Infly released OpenCoder: 1.5B and 8B coding models with instruction SFT'd versions and their datasets! ๐Ÿ’—

๐Ÿ–ผ๏ธ Image/Video Gen: Alibaba vision lab released In-context LoRA -- 10 LoRA models on different themes based on Flux. Also Mochi the sota video generation model with A2.0 license now comes natively supported in diffusers ๐Ÿ‘

๐Ÿ–ผ๏ธ VLMs/Multimodal: NexaAIDev released Omnivision 968M a new vision language model aligned with DPO for reducing hallucinations, also comes with GGUF ckpts ๐Ÿ‘ Microsoft released LLM2CLIP, a new CLIP-like model with longer context window allowing complex text inputs and better search

๐ŸŽฎ AGI?: Etched released Oasis 500M, a diffusion based open world model that takes keyboard input and outputs gameplay ๐Ÿคฏ

Datasets
Common Corpus: A text dataset with 2T tokens with permissive license for EN/FR on various sources: code, science, finance, culture ๐Ÿ“–