The Hugging Face Transformers ↔️ vLLM integration just leveled up: Vision-Language Models are now supported out of the box! If the model is integrated into Transformers, you can now run it directly with vLLM. github.com/vllm-project/v… Great work Raushan Turganbay 👏

Hugging Face just dropped Trending Papers partnered with AI at Meta and Papers with Code to build a successor to papers with code (which was sunsetted yesterday) HF papers provides a new section for the community to follow trending Papers, linked to their code implementations

With the latest release, I want to make sure I get this message to the community: we are listening! Hugging Face we are very ambitious and we want `transformers` to accelerate the ecosystem and enable all hardwares / platforms! Let's build AGI together 🫣 Unbloat and Enable!

Hugging Face 🤝 Jan You can now use Hugging Face as a remote model provider in Jan. Go to Settings -> Model Providers -> add your Hugging Face API key. Then open a new chat and pick a model from Hugging Face. Works with any model in Hugging Face in Jan.

🚀 𝐄𝐱𝐜𝐢𝐭𝐢𝐧𝐠 𝐍𝐞𝐰𝐬! 𝐏𝐲𝐏𝐈 𝐚𝐧𝐝 𝐆𝐢𝐭𝐇𝐮𝐛 𝐑𝐞𝐥𝐞𝐚𝐬𝐞 𝐟𝐨𝐫 𝐋𝐞𝐑𝐨𝐛𝐨𝐭 🚀 We’re thrilled to announce that we have reached a new major milestone, the first 𝐨𝐟𝐟𝐢𝐜𝐢𝐚𝐥 𝐏𝐲𝐏𝐈 and 𝐆𝐢𝐭𝐇𝐮𝐛 𝐑𝐞𝐥𝐞𝐚𝐬𝐞! 🎉 * You can now install LeRobot with a

All the details of OpenAI's new base model courtesy of HuggingFace update log. - Looks like NO base model (despite their oss model cookbook page saying it is) - 21B and 117B Total Param, 3.6B and 5.1B Active MoE Model sizes - Reasoning and Agentic capabilities - License: APACHE

gpt-oss is out! we made an open model that performs at the level of o4-mini and runs on a high-end laptop (WTF!!) (and a smaller one that runs on a phone). super proud of the team; big triumph of technology.

HUGE: OpenAI just released GPT OSS on Hugging Face! 🤯 Here's what you need to know: 1. Two models: gpt-oss-20b and gpt-oss-120b, designed for powerful reasoning, agentic tasks, and more! 2. Mixture-of-experts (MoE) architecture: 21B and 117B total parameters, with 3.6B and 5.1B

GPT OSS is out. It's OpenAI's first open-weights model release since GPT-2, and some of the technical innovations have huge implications. This is a thread about two of them: Learned attention sinks, and MXFP4 weights.

When Sam Altman told me at the AI summit in Paris that they were serious about releasing open-source models & asked what would be useful, I couldn’t believe it. But six months of collaboration later, here it is: Welcome to OSS-GPT on Hugging Face! It comes in two sizes, for both

OpenAI just released GPT-OSS: An Open Source Language Model on Hugging Face Open source meaning: 💸 Free 🔒 Private 🔧 Customizable

Please don’t download the weights all at once 🙏 or our servers will melt

Welcome to OpenAI on Hugging Face!

The new GPT-OSS models are Mixture of Experts (MoEs), with 20B and 120B parameters. Since expert weights make up ~90% of the model, OpenAI decided to quantize them to 4 bits during post-training using the MXFP4 standard. Quantizing these to MXFP4 enables the larger model to

🚀 LlamaFactory now supports the fine-tuning of GPT-OSS models. Check out this thread to get started in 10 minutes 🤗 github.com/hiyouga/LLaMA-…

We have cooked some something nice with Axolotl for 🤗 accelerate v1.10. Have you ever wanted to train a large model, but couldn't setup your env? Current multi-gpu frameworks are hard to install, the configuration has like 100 options. Here comes ParallelismConfig 🚀 1/5 🧵

This is by far my favorite feature so far this year. Unlocks a lot of exciting possibilities for post-training larger models in the Hugging Face ecosystem such as improved multi-node and slurm support.