Hugging Face (Twitter)
RT @Xianbao_QIAN: This work from @BytedanceTalk seed team will be transformative and open the era of iterative latent reasoning:
why do model have to only think in human languages?
At least I don't.
The result is also significant:
- 2.6B R4 (4 steps) model achieved comparable performance with qwen3 8B and Gemma 3 12B
The project was supervised by @Yoshua_Bengio @jasoneshraghian How do you feel about this work?
RT @Xianbao_QIAN: This work from @BytedanceTalk seed team will be transformative and open the era of iterative latent reasoning:
why do model have to only think in human languages?
At least I don't.
The result is also significant:
- 2.6B R4 (4 steps) model achieved comparable performance with qwen3 8B and Gemma 3 12B
The project was supervised by @Yoshua_Bengio @jasoneshraghian How do you feel about this work?
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Hugging Face (Twitter)
RT @allen_ai: Introducing OlmoEarth π, state-of-the-art AI foundation models paired with ready-to-use open infrastructure to turn Earth data into clear, up-to-date insights within hoursβnot years.
RT @allen_ai: Introducing OlmoEarth π, state-of-the-art AI foundation models paired with ready-to-use open infrastructure to turn Earth data into clear, up-to-date insights within hoursβnot years.
Hugging Face (Twitter)
RT @ClementDelangue: When you run AI on your device, it is more efficient and less big brother and free!
So it's very cool to see the new llama.cpp UI, a chatgpt-like app that fully runs on your laptop without needing wifi or sending any data external to any API.
It supports:
- 150,000+ GGUF models
- Drop in PDFs, images, or text documents
- Branch and edit conversations anytime
- Parallel chats and image processing
- Math and code rendering
- Constrained generation with JSON schema supported
Well done @ggerganov and team!
RT @ClementDelangue: When you run AI on your device, it is more efficient and less big brother and free!
So it's very cool to see the new llama.cpp UI, a chatgpt-like app that fully runs on your laptop without needing wifi or sending any data external to any API.
It supports:
- 150,000+ GGUF models
- Drop in PDFs, images, or text documents
- Branch and edit conversations anytime
- Parallel chats and image processing
- Math and code rendering
- Constrained generation with JSON schema supported
Well done @ggerganov and team!
Hugging Face (Twitter)
RT @_lewtun: Or ... you could just host them on hf.co https://twitter.com/AnthropicAI/status/1985752012189728939#m
RT @_lewtun: Or ... you could just host them on hf.co https://twitter.com/AnthropicAI/status/1985752012189728939#m
Hugging Face (Twitter)
RT @victormustar: New: Qwen-Image-2509-MultipleAngles. Very solid model and probably a lot of creative use cases to find with it.
β¬οΈ Free demo available on Hugging Face
RT @victormustar: New: Qwen-Image-2509-MultipleAngles. Very solid model and probably a lot of creative use cases to find with it.
β¬οΈ Free demo available on Hugging Face
Hugging Face (Twitter)
RT @alvarobartt: One of the best parts of working at @huggingface is seeing how much the community drives open-source forward. On Text Embeddings Inference (TEI), we're just one PR away from 300 contributions thanks to all the people who've helped make embedding inference and serving better, faster, and safer.
Nice reminder that open-source only works because people care enough to build together.
RT @alvarobartt: One of the best parts of working at @huggingface is seeing how much the community drives open-source forward. On Text Embeddings Inference (TEI), we're just one PR away from 300 contributions thanks to all the people who've helped make embedding inference and serving better, faster, and safer.
Nice reminder that open-source only works because people care enough to build together.
βHugging Face (Twitter)
RT @willmcgugan: Thank you @huggingface for sponsoring me on @github. You can join them at my sponsors profile:
RT @willmcgugan: Thank you @huggingface for sponsoring me on @github. You can join them at my sponsors profile:
GitHub
Sponsor @willmcgugan on GitHub Sponsors
My name is Will. I am a software engineer and technical author with over 30 years of experience. My Open Source software has been downloaded more than 3 billion times π€―.
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Hugging Face (Twitter)
RT @multimodalart: Qwen Image Multiple Angles LoRA is an exquisitely trained LoRA! πΛββ§κ°α
Keep character and scenes consistent, and flies the camera around! Open source got there! One of the best LoRAs I've come across lately π
RT @multimodalart: Qwen Image Multiple Angles LoRA is an exquisitely trained LoRA! πΛββ§κ°α
Keep character and scenes consistent, and flies the camera around! Open source got there! One of the best LoRAs I've come across lately π
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Hugging Face (Twitter)
RT @chichengcc: Can we collect robot data without any robots?
Introducing Universal Manipulation Interface (UMI)
An open-source $400 system from @Stanford designed to democratize robot data collection
0 teleop -> autonomously wash dishes (precise), toss (dynamic), and fold clothes (bimanual)
RT @chichengcc: Can we collect robot data without any robots?
Introducing Universal Manipulation Interface (UMI)
An open-source $400 system from @Stanford designed to democratize robot data collection
0 teleop -> autonomously wash dishes (precise), toss (dynamic), and fold clothes (bimanual)
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Hugging Face (Twitter)
RT @linoy_tsaban: adding camera control to the list of things Qwen Image Edit is great at
+ with a specialized multi-angle LoRA it's even betterβ¨
> rotate the camera
> tilt between birdβs-eye and wormβs-eye views
> adjust lens (wide, close-up)
of course we built a demo for it π€πΉ
RT @linoy_tsaban: adding camera control to the list of things Qwen Image Edit is great at
+ with a specialized multi-angle LoRA it's even betterβ¨
> rotate the camera
> tilt between birdβs-eye and wormβs-eye views
> adjust lens (wide, close-up)
of course we built a demo for it π€πΉ
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Hugging Face (Twitter)
RT @andimarafioti: Mixing vision and robotics is incredibly hard, but when it finally works it feels like magic.
RT @andimarafioti: Mixing vision and robotics is incredibly hard, but when it finally works it feels like magic.
Hugging Face (Twitter)
RT @lhoestq: Just released today ! Full support for dataset streaming in large scale distributed training
With datasets==4.4.1 and huggingface_hub==1.1.0, better than 4.4 and 1.0
These include all the features explained in the blog post https://huggingface.co/blog/streaming-datasets
Advanced examples in replies:
RT @lhoestq: Just released today ! Full support for dataset streaming in large scale distributed training
With datasets==4.4.1 and huggingface_hub==1.1.0, better than 4.4 and 1.0
These include all the features explained in the blog post https://huggingface.co/blog/streaming-datasets
Advanced examples in replies:
Hugging Face (Twitter)
RT @Kimi_Moonshot: π Hello, Kimi K2 Thinking!
The Open-Source Thinking Agent Model is here.
πΉ SOTA on HLE (44.9%) and BrowseComp (60.2%)
πΉ Executes up to 200 β 300 sequential tool calls without human interference
πΉ Excels in reasoning, agentic search, and coding
πΉ 256K context window
Built as a thinking agent, K2 Thinking marks our latest efforts in test-time scaling β scaling both thinking tokens and tool-calling turns.
K2 Thinking is now live on kimi.com in chat mode, with full agentic mode coming soon. It is also accessible via API.
π API is live: platform.moonshot.ai
π Tech blog: https://moonshotai.github.io/Kimi-K2/thinking.html
π Weights & code: huggingface.co/moonshotai
RT @Kimi_Moonshot: π Hello, Kimi K2 Thinking!
The Open-Source Thinking Agent Model is here.
πΉ SOTA on HLE (44.9%) and BrowseComp (60.2%)
πΉ Executes up to 200 β 300 sequential tool calls without human interference
πΉ Excels in reasoning, agentic search, and coding
πΉ 256K context window
Built as a thinking agent, K2 Thinking marks our latest efforts in test-time scaling β scaling both thinking tokens and tool-calling turns.
K2 Thinking is now live on kimi.com in chat mode, with full agentic mode coming soon. It is also accessible via API.
π API is live: platform.moonshot.ai
π Tech blog: https://moonshotai.github.io/Kimi-K2/thinking.html
π Weights & code: huggingface.co/moonshotai
Hugging Face (Twitter)
RT @hanouticelina: We're definitely not slowing down - it's only been 2 weeks since v1.0, but πππππππππππ_πππ v1.1 is already here packed with a lot of nice features! π₯
This update brings a faster and cleaner download experience and new powerful features to the Hugging Face CLI!
$ πππ πππππππ πππππππππππ_πππ --πππππππ
π§΅See what's new in the thread below π
RT @hanouticelina: We're definitely not slowing down - it's only been 2 weeks since v1.0, but πππππππππππ_πππ v1.1 is already here packed with a lot of nice features! π₯
This update brings a faster and cleaner download experience and new powerful features to the Hugging Face CLI!
$ πππ πππππππ πππππππππππ_πππ --πππππππ
π§΅See what's new in the thread below π
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Hugging Face (Twitter)
RT @Wauplin: Using the hf CLI just got insanely easy:
uvx hf auth login
uvx hf download
uvx hf ...
Always runs the latest version in an isolated environment. No install or updates required thanks to @astral_sh 's awesome tooling!
RT @Wauplin: Using the hf CLI just got insanely easy:
uvx hf auth login
uvx hf download
uvx hf ...
Always runs the latest version in an isolated environment. No install or updates required thanks to @astral_sh 's awesome tooling!
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Hugging Face (Twitter)
RT @jadechoghari: We're introducing EnvHub to LeRobot!
Upload simulation environments to the @hugginigface hub, and load them in lerobot, with one line of code !
env = lerobot.make_env("username/my-env", trust_remote_code=True)
Back in 2017, @OpenAI called on the community to build Gym environments.
Today, we're doing the same for robotics.
We're calling researchers, students, hobbyists, labs, and startups to publish complex envs, tasks, and benchmarks on the Hub, so we see how robot policies perform. (in Isaaac, Mujoco, Genesis, etc..)
Fill out and submit the form linked in the comments to join the effort!
RT @jadechoghari: We're introducing EnvHub to LeRobot!
Upload simulation environments to the @hugginigface hub, and load them in lerobot, with one line of code !
env = lerobot.make_env("username/my-env", trust_remote_code=True)
Back in 2017, @OpenAI called on the community to build Gym environments.
Today, we're doing the same for robotics.
We're calling researchers, students, hobbyists, labs, and startups to publish complex envs, tasks, and benchmarks on the Hub, so we see how robot policies perform. (in Isaaac, Mujoco, Genesis, etc..)
Fill out and submit the form linked in the comments to join the effort!
Hugging Face (Twitter)
RT @lunarflu1: 2025 update: We now have 12 different free courses available on @huggingface !
Check it out here:
hf.co/learn
RT @lunarflu1: 2025 update: We now have 12 different free courses available on @huggingface !
Check it out here:
hf.co/learn
Hugging Face (Twitter)
RT @abidlabs: I'm working on getting more developers to build software with open-weight models and open-source tooling. Not always easy to change entrenched software developer behavior but if we are able to, a lot of good will come out of it. Looking for help, DM me if you're interested!
RT @abidlabs: I'm working on getting more developers to build software with open-weight models and open-source tooling. Not always easy to change entrenched software developer behavior but if we are able to, a lot of good will come out of it. Looking for help, DM me if you're interested!
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Hugging Face (Twitter)
Best practices for testing your Gradio app π https://twitter.com/abidlabs/status/1986528919017955837#m
Best practices for testing your Gradio app π https://twitter.com/abidlabs/status/1986528919017955837#m
Hugging Face (Twitter)
RT @ben_burtenshaw: you can now push, run, and pull agentic environments from the hugging face hub as spaces.
the workflow looks like this:
- do `openenv init` to start a new environment from a template
- build/port your rl environment
- use `openenv push` to push the environment to hub.
- from there, you can either call the api directly
- or, just pull it as a locally running docker container. mmmm
can't wait to see rl environments get super open
RT @ben_burtenshaw: you can now push, run, and pull agentic environments from the hugging face hub as spaces.
the workflow looks like this:
- do `openenv init` to start a new environment from a template
- build/port your rl environment
- use `openenv push` to push the environment to hub.
- from there, you can either call the api directly
- or, just pull it as a locally running docker container. mmmm
can't wait to see rl environments get super open