Hugging Face (Twitter)
RT @ailozovskaya: Reachy Mini was on stage for the first time! @TEDAIVienna
It proved it can be a real improv actor! Did you see it? What did you think of the show? Maybe itβs the first robot actor ππ»
https://huggingface.co/blog/reachy-mini
RT @ailozovskaya: Reachy Mini was on stage for the first time! @TEDAIVienna
It proved it can be a real improv actor! Did you see it? What did you think of the show? Maybe itβs the first robot actor ππ»
https://huggingface.co/blog/reachy-mini
This media is not supported in your browser
VIEW IN TELEGRAM
Hugging Face (Twitter)
RT @ClementDelangue: As Jensen mentioned with @altcap @BG2Pod @bgurley, something that few people know is that @nvidia is becoming the American open-source leader in AI, with over 300 contributions of models, datasets and apps on @huggingface in the past year.
And I have a feeling they're just getting started!
RT @ClementDelangue: As Jensen mentioned with @altcap @BG2Pod @bgurley, something that few people know is that @nvidia is becoming the American open-source leader in AI, with over 300 contributions of models, datasets and apps on @huggingface in the past year.
And I have a feeling they're just getting started!
This media is not supported in your browser
VIEW IN TELEGRAM
Hugging Face (Twitter)
RT @charmcli: If you love open models, youβll love this: Crush now runs with @huggingface Inference Providers π€β¨
RT @charmcli: If you love open models, youβll love this: Crush now runs with @huggingface Inference Providers π€β¨
Hugging Face (Twitter)
RT @Xianbao_QIAN: The largest 80B open source image generation model has been dropped on @huggingface !
Review video by AIWood below. https://twitter.com/Xianbao_QIAN/status/1971577053872099791#m
RT @Xianbao_QIAN: The largest 80B open source image generation model has been dropped on @huggingface !
Review video by AIWood below. https://twitter.com/Xianbao_QIAN/status/1971577053872099791#m
Hugging Face (Twitter)
RT @RisingSayak: Feeling so happy that we got accepted to #NeurIPS2025 π
This was a genuinely fulfilling piece of work, and a lot of knobs needed tinkering with.
Check out the thread below for more details! https://twitter.com/RisingSayak/status/1933481434020565437#m
RT @RisingSayak: Feeling so happy that we got accepted to #NeurIPS2025 π
This was a genuinely fulfilling piece of work, and a lot of knobs needed tinkering with.
Check out the thread below for more details! https://twitter.com/RisingSayak/status/1933481434020565437#m
Hugging Face (Twitter)
RT @RisingSayak: Today, we're shipping native support for context-parallelism to help make diffusion inference go brrr on multiple GPUs π
Our CP API is made to work with two flavors of distributed attention: Ring & Ulysses.
Huge thanks to @aryanvs_ for shipping this!
Deets β¬οΈ
RT @RisingSayak: Today, we're shipping native support for context-parallelism to help make diffusion inference go brrr on multiple GPUs π
Our CP API is made to work with two flavors of distributed attention: Ring & Ulysses.
Huge thanks to @aryanvs_ for shipping this!
Deets β¬οΈ
βHugging Face (Twitter)
RT @Shekswess: Tiny Reasoning Language Model (trlm-135) β‘
A 135M parameter experiment to see if small models can learn structured reasoning with the right data + training strategy.
π³ Model Card:
RT @Shekswess: Tiny Reasoning Language Model (trlm-135) β‘
A 135M parameter experiment to see if small models can learn structured reasoning with the right data + training strategy.
π³ Model Card:
X (formerly Twitter)
Shekswess (@Shekswess) on X
Tiny Reasoning Language Model (trlm-135) β‘
A 135M parameter experiment to see if small models can learn structured reasoning with the right data + training strategy.
π³ Model Card: https://t.co/PiXhLyJbH8
A 135M parameter experiment to see if small models can learn structured reasoning with the right data + training strategy.
π³ Model Card: https://t.co/PiXhLyJbH8
Hugging Face (Twitter)
RT @not_so_lain: Iβm both honored and humbled to have crossed 3.000 followers on @huggingface π₯
When I first started, I never imagined this community would become such a big part of my journey.
Thank you to everyone who has read my work or collaborated with me. Your support keeps me goingβ¨
RT @not_so_lain: Iβm both honored and humbled to have crossed 3.000 followers on @huggingface π₯
When I first started, I never imagined this community would become such a big part of my journey.
Thank you to everyone who has read my work or collaborated with me. Your support keeps me goingβ¨
Hugging Face (Twitter)
RT @ClementDelangue: The gdpval dataset from @OpenAI is number one trending on @huggingface this week!
RT @ClementDelangue: The gdpval dataset from @OpenAI is number one trending on @huggingface this week!
βHugging Face (Twitter)
RT @linoy_tsaban: still getting over the fact HunyuanImage 3.0 is here (less than a month since HunyuanIamge 2.1) and then I see it's 80B params π€―
+ Image editing is coming π
FUN TIMES
https://huggingface.co/tencent/HunyuanImage-3.0
RT @linoy_tsaban: still getting over the fact HunyuanImage 3.0 is here (less than a month since HunyuanIamge 2.1) and then I see it's 80B params π€―
+ Image editing is coming π
FUN TIMES
https://huggingface.co/tencent/HunyuanImage-3.0
huggingface.co
tencent/HunyuanImage-3.0 Β· Hugging Face
Weβre on a journey to advance and democratize artificial intelligence through open source and open science.
Hugging Face (Twitter)
RT @multimodalart: the π³ππΉπ¨ π£π―π’π·π«π¦ is LIVE
Train Qwen, Wan and FLUX LoRAs for free for 1 week (Sep 29 - Oct 6th)
We cobbled together @ostrisai AI Toolkit & the new @huggingface Jobs API together
RT @multimodalart: the π³ππΉπ¨ π£π―π’π·π«π¦ is LIVE
Train Qwen, Wan and FLUX LoRAs for free for 1 week (Sep 29 - Oct 6th)
We cobbled together @ostrisai AI Toolkit & the new @huggingface Jobs API together
Hugging Face (Twitter)
RT @Saboo_Shubham_: oLLM is a lightweight Python library for local large-context LLM inference.
Run gpt-oss-20B, Qwen3-next-80B, Llama-3.1-8B on ~$200 consumer GPU with just 8GB VRAM. And this is without any quantization - only fp16/bf16 precision.
100% Opensource.
RT @Saboo_Shubham_: oLLM is a lightweight Python library for local large-context LLM inference.
Run gpt-oss-20B, Qwen3-next-80B, Llama-3.1-8B on ~$200 consumer GPU with just 8GB VRAM. And this is without any quantization - only fp16/bf16 precision.
100% Opensource.
Hugging Face (Twitter)
RT @_akhaliq: HunyuanImage 3.0 is out on Hugging Face
A Powerful Native Multimodal Model for Image Generation
80B parameters, Largest Image Generation MoE Model
Reasons with world knowledge
Generates text within images
vibe coded a text to image app with anycoder using @fal
RT @_akhaliq: HunyuanImage 3.0 is out on Hugging Face
A Powerful Native Multimodal Model for Image Generation
80B parameters, Largest Image Generation MoE Model
Reasons with world knowledge
Generates text within images
vibe coded a text to image app with anycoder using @fal
This media is not supported in your browser
VIEW IN TELEGRAM
Hugging Face (Twitter)
RT @reach_vb: Introducing Hugging Face Inference Provider Starter App π₯
Built w/ @nextjs and @OpenAIDevs SDK - powered by SoTA open-weights LLMs π€
Create seamless experiences without worrying about boilerplate via streaming and structured outputs
Check out the app in comments below π
RT @reach_vb: Introducing Hugging Face Inference Provider Starter App π₯
Built w/ @nextjs and @OpenAIDevs SDK - powered by SoTA open-weights LLMs π€
Create seamless experiences without worrying about boilerplate via streaming and structured outputs
Check out the app in comments below π
This media is not supported in your browser
VIEW IN TELEGRAM
Hugging Face (Twitter)
RT @dylan_ebert_: I made a vibe coding game engine
the problem: people are trying to vibe code games. it kind of works at first, but as the project grows, things begin to fall apart
why? and what can we do about it? ‡οΈ
step 1.
RT @dylan_ebert_: I made a vibe coding game engine
the problem: people are trying to vibe code games. it kind of works at first, but as the project grows, things begin to fall apart
why? and what can we do about it? ‡οΈ
step 1.
Hugging Face (Twitter)
RT @NousResearch: Starting today, Psyche will train 6 new models in parallel in pursuit of creating world class open source AI.
These runs serve as the starting point for future experiments and a more thorough and empirical training process.
RT @NousResearch: Starting today, Psyche will train 6 new models in parallel in pursuit of creating world class open source AI.
These runs serve as the starting point for future experiments and a more thorough and empirical training process.
Hugging Face (Twitter)
RT @osanseviero: Welcome to TimesFM 2.5, a pre-trained model for times-series forecasting, which performs great in zero-shot out-of-the-box
- 200M params (down from 500M)
- 16k context (up from 2k)
- Available on Hugging Face
- Apache 2.0
Happy Monday!
RT @osanseviero: Welcome to TimesFM 2.5, a pre-trained model for times-series forecasting, which performs great in zero-shot out-of-the-box
- 200M params (down from 500M)
- 16k context (up from 2k)
- Available on Hugging Face
- Apache 2.0
Happy Monday!
This media is not supported in your browser
VIEW IN TELEGRAM
Hugging Face (Twitter)
RT @ting_: DeepSeek-V3.2-Exp is live on @huggingface API, supported by @novita_labs π€
β‘ More efficient long-context reasoning
π Matches V3.1 performance, even surpasses on tasks like AIME 2025 & Codeforces
π Content window 163K
β Structured Output, Function Calling, Reasoning
Tryπ
RT @ting_: DeepSeek-V3.2-Exp is live on @huggingface API, supported by @novita_labs π€
β‘ More efficient long-context reasoning
π Matches V3.1 performance, even surpasses on tasks like AIME 2025 & Codeforces
π Content window 163K
β Structured Output, Function Calling, Reasoning
Tryπ
Hugging Face (Twitter)
RT @AntLingAGI: π Ring-1T-preview: Deep Thinking, No Waiting
The first 1 trillion open-source thinking model
-> Early results in natural language: AIME25/92.6, HMMT25/84.5, ARC-AGI-1/50.8, LCB/78.3, CF/94.7
-> Solved IMO25 Q3 in one shot, with partial solutions for Q1/Q2/Q4/Q5
Still evolving!
RT @AntLingAGI: π Ring-1T-preview: Deep Thinking, No Waiting
The first 1 trillion open-source thinking model
-> Early results in natural language: AIME25/92.6, HMMT25/84.5, ARC-AGI-1/50.8, LCB/78.3, CF/94.7
-> Solved IMO25 Q3 in one shot, with partial solutions for Q1/Q2/Q4/Q5
Still evolving!