Hugging Face
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Hugging Face (Twitter)

RT @vanstriendaniel: You can now generate synthetic data using @OpenAI's GPT OSS models on @huggingface Jobs!

One command, no setup:

hf jobs uv run --flavor l4x4 [script-url] \
--input-dataset your/dataset \
--output-dataset your/output

Works on L4 GPUs

https://huggingface.co/datasets/uv-scripts/openai-oss
Hugging Face (Twitter)

RT @MaziyarPanahi: 🚀 In under 10 hours, both gpt-oss models from @OpenAI are now trending at #1 and #2 on @huggingface!

Openness wins again.

@sama, can you feel the love tonight? 🎶
Hugging Face (Twitter)

RT @wjb_mattingly: Woot! First finetune of Dots.OCR on @huggingface ! Haven't done this since Qwen 2 VL. I'll be sharing the finetuning script tomorrow.
Hugging Face (Twitter)

RT @cline: Live in Cline via @huggingface: gpt-oss-120b & gpt-oss-20b

> gpt-oss-120b is built for production-grade applications with high reasoning capabilities
> gpt-oss-20b is for lower latency needs and specialized local use cases

Also accessible via the Cline & OpenRouter providers
Hugging Face (Twitter)

RT @reach_vb: Want to run the latest @OpenAI gpt-oss models with Continuous Batching, Tensor Parallelism, Flash Attention 3 and more?

Checkout our detailed Inference and Fine-tuning recipes 🤗
Hugging Face (Twitter)

RT @ClementDelangue: Lots of conflicting takes about gpt-oss (yay open-source in the spotlight)!

We’re powering the official @openai demo gpt-oss.com with HF inference providers thanks to @FireworksAI_HQ, @CerebrasSystems, @GroqInc and @togethercompute so we have a front-row seat of what’s happening.

Something to remember: inference for new frontier open models isn’t easy, especially with a new format like harmony and the volume of interest that gpt-oss is getting out of the gate.

Early spikes can temporarily affect quality, accuracy, and overall "vibes," particularly just 24 hours post-release when providers are racing against the clock with barely any sleep!

Some advice to avoid forming the wrong opinions:

- If you care about getting vibes as fast as possible, use a hosted setup that gives you a diversity of providers like HF inference providers (https://huggingface.co/docs/inference-providers/guides/gpt-oss) and follow official standard...

Перейти на оригинальный пост
Hugging Face (Twitter)

RT @elonmusk: @BasedBeffJezos: It’s high time we open sourced Grok 2. Will make it happen next week.

We’ve just been fighting fires and burning the 4am oil nonstop for a while now.
Hugging Face (Twitter)

RT @romainhuet: Great perspective and tips from @ClementDelangue on the early days of gpt-oss.

Building strong foundations take time, and we’re excited to be working with inference providers and @huggingface to help these models perform at their best. Please keep your feedback coming! https://twitter.com/ClementDelangue/status/1953119901649891367#m
Hugging Face (Twitter)

RT @romainhuet: Both gpt-oss models are trending #1 and #2 among 2M models on @huggingface! 🤗 Thanks to the open-source AI community for your support since launch.

We’re following discussions and will pop in when we can—feel free to ask questions, share ideas, and show what you’re building!
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Hugging Face (Twitter)

RT @roo_code: ICYMI: Roo Code now integrates with Hugging Face 🤗

Plug in your API key, explore 90+ models, and run them directly from your editor—no wrappers, no token copy-paste.

Try it now!
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Hugging Face (Twitter)

RT @reach_vb: BOOOOM! You can now run @OpenAI gpt-oss 20B natively in @GoogleColab T4 for FREE! 🔥

Powered by Transformers

The setup takes a bit since everything is bleeding edge, but once done it should work as expected

Link to our cookbook in comments 👇
Hugging Face (Twitter)

RT @calebfahlgren: The @huggingface trending is filled with absolute bangers 😮‍💨
Hugging Face (Twitter)

RT @mervenoyann: new TRL comes with GRPO & MPO support for vision language models 💥

we also dropped an explainer on them & how to train with one-liner CLI commands 🫡
Hugging Face (Twitter)

RT @abidlabs: Don't lock in your experiment tracking data into proprietary vendors!

With Trackio, all of your metrics are stored in a (public or private, you choose) Hugging Face Dataset, so that you can export them at any time!

https://github.com/gradio-app/trackio