Hugging Face (Twitter)
RT @reach_vb: The Hugging Face Hub team is on a tear recently:
> You can create custom apps with domains on spaces
> Edit GGUF metadata on the Fly
> 100% of the Hub is powered by Xet - faster, efficient
> Responses API support for ALL Inference Providers
> MCP-UI support for HF MCP Server
> Search papers based on the Org
> Showcase repository size on the UI
and a lot more - excited for the coming weeks/ months as we continue to improve the overall UX! 🤗
RT @reach_vb: The Hugging Face Hub team is on a tear recently:
> You can create custom apps with domains on spaces
> Edit GGUF metadata on the Fly
> 100% of the Hub is powered by Xet - faster, efficient
> Responses API support for ALL Inference Providers
> MCP-UI support for HF MCP Server
> Search papers based on the Org
> Showcase repository size on the UI
and a lot more - excited for the coming weeks/ months as we continue to improve the overall UX! 🤗
Hugging Face (Twitter)
RT @victormustar: Microsoft did something interesting here 👀
“Unlike typical LLMs that are trained to play the role of the "assistant" in conversation, we trained UserLM-8b to simulate the “user” role in conversation”
https://huggingface.co/microsoft/UserLM-8b
RT @victormustar: Microsoft did something interesting here 👀
“Unlike typical LLMs that are trained to play the role of the "assistant" in conversation, we trained UserLM-8b to simulate the “user” role in conversation”
https://huggingface.co/microsoft/UserLM-8b
huggingface.co
microsoft/UserLM-8b · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Hugging Face (Twitter)
RT @ClementDelangue: Refreshing to see @neuphonicspeech, a London-based seed startup that raised just a few million, top the most trending models on @huggingface today. They manage to stand out amongst 2M public models & giant corporations from the US and China.
Good example that everyone can contribute meaningfully to open-source (and get great visibility and credibility thanks to it) no matter their size, location or compute budgets. We need more of this!
RT @ClementDelangue: Refreshing to see @neuphonicspeech, a London-based seed startup that raised just a few million, top the most trending models on @huggingface today. They manage to stand out amongst 2M public models & giant corporations from the US and China.
Good example that everyone can contribute meaningfully to open-source (and get great visibility and credibility thanks to it) no matter their size, location or compute budgets. We need more of this!
Hugging Face (Twitter)
RT @ClementDelangue: So proud to see Reachy Mini named one of the Best Inventions of 2025 by @TIME!
Huge credit to the @pollenrobotics and @huggingface teams, turning a concept into thousands of units sold and shipped in under 6 months.
We might not be as slick as some other robotics companies (we sure don't do such good marketing videos and demos), but if we hit 100,000 Reachy Minis next year and 1 million by 2027, we’ll have a real shot at transforming robotics and AI through open-source and collaboration.
We’re just getting started 🦾🦾🦾
RT @ClementDelangue: So proud to see Reachy Mini named one of the Best Inventions of 2025 by @TIME!
Huge credit to the @pollenrobotics and @huggingface teams, turning a concept into thousands of units sold and shipped in under 6 months.
We might not be as slick as some other robotics companies (we sure don't do such good marketing videos and demos), but if we hit 100,000 Reachy Minis next year and 1 million by 2027, we’ll have a real shot at transforming robotics and AI through open-source and collaboration.
We’re just getting started 🦾🦾🦾
Hugging Face (Twitter)
RT @xeophon_: nvidia is the western qwen in terms of open releases but yall are not ready for this conversation
RT @xeophon_: nvidia is the western qwen in terms of open releases but yall are not ready for this conversation
Hugging Face (Twitter)
RT @abacaj: Pretty bullish on LoRA fine tuning again. Idk if it’s because the models are so much better today that they adapt much more easily or what... someone should study this
RT @abacaj: Pretty bullish on LoRA fine tuning again. Idk if it’s because the models are so much better today that they adapt much more easily or what... someone should study this
Hugging Face (Twitter)
RT @mervenoyann: meet-up next month at @huggingface Paris office with our friends at @bfl_ml and @fal 🇫🇷🥖🤗
talks, networking, food, swag 🕺🏻are you in? 🤝
RT @mervenoyann: meet-up next month at @huggingface Paris office with our friends at @bfl_ml and @fal 🇫🇷🥖🤗
talks, networking, food, swag 🕺🏻are you in? 🤝
Hugging Face (Twitter)
RT @pollenrobotics: The first Reachy Mini units are on their way! 🚀
Our Community Beta Program is starting soon — selected testers will receive their robots to help us improve docs, software & explore new features.
Lite & Wireless versions ship around Dec 15!
RT @pollenrobotics: The first Reachy Mini units are on their way! 🚀
Our Community Beta Program is starting soon — selected testers will receive their robots to help us improve docs, software & explore new features.
Lite & Wireless versions ship around Dec 15!
Hugging Face (Twitter)
RT @ClementDelangue: It's easier than ever to train, optimize and run your own models thanks to open-source (versus delegating all learning, control, capabilities to black-box APIs).
Cool to see @karpathy proving it once more by leveraging @huggingface fineweb (https://huggingface.co/datasets/karpathy/fineweb-edu-100b-shuffle)! https://twitter.com/karpathy/status/1977755427569111362#m
RT @ClementDelangue: It's easier than ever to train, optimize and run your own models thanks to open-source (versus delegating all learning, control, capabilities to black-box APIs).
Cool to see @karpathy proving it once more by leveraging @huggingface fineweb (https://huggingface.co/datasets/karpathy/fineweb-edu-100b-shuffle)! https://twitter.com/karpathy/status/1977755427569111362#m
Hugging Face (Twitter)
RT @BdsLoick: New blog post analyzing the top 50 entities with the most downloaded models on @huggingface 🤗!
The purpose here is to get an idea of the profile of the models with the greatest impact in open source (we are not interested in closed models here!).
Some key findings:
RT @BdsLoick: New blog post analyzing the top 50 entities with the most downloaded models on @huggingface 🤗!
The purpose here is to get an idea of the profile of the models with the greatest impact in open source (we are not interested in closed models here!).
Some key findings:
Hugging Face (Twitter)
RT @karpathy: Excited to release new repo: nanochat!
(it's among the most unhinged I've written).
Unlike my earlier similar repo nanoGPT which only covered pretraining, nanochat is a minimal, from scratch, full-stack training/inference pipeline of a simple ChatGPT clone in a single, dependency-minimal codebase. You boot up a cloud GPU box, run a single script and in as little as 4 hours later you can talk to your own LLM in a ChatGPT-like web UI.
It weighs ~8,000 lines of imo quite clean code to:
- Train the tokenizer using a new Rust implementation
- Pretrain a Transformer LLM on FineWeb, evaluate CORE score across a number of metrics
- Midtrain on user-assistant conversations from SmolTalk, multiple choice questions, tool use.
- SFT, evaluate the chat model on world knowledge multiple choice (ARC-E/C, MMLU), math (GSM8K), code (HumanEval)
- RL the model optionally on GSM8K with "GRPO"
- Efficient inference the model in an Engine with KV cache,...
Перейти на оригинальный пост
RT @karpathy: Excited to release new repo: nanochat!
(it's among the most unhinged I've written).
Unlike my earlier similar repo nanoGPT which only covered pretraining, nanochat is a minimal, from scratch, full-stack training/inference pipeline of a simple ChatGPT clone in a single, dependency-minimal codebase. You boot up a cloud GPU box, run a single script and in as little as 4 hours later you can talk to your own LLM in a ChatGPT-like web UI.
It weighs ~8,000 lines of imo quite clean code to:
- Train the tokenizer using a new Rust implementation
- Pretrain a Transformer LLM on FineWeb, evaluate CORE score across a number of metrics
- Midtrain on user-assistant conversations from SmolTalk, multiple choice questions, tool use.
- SFT, evaluate the chat model on world knowledge multiple choice (ARC-E/C, MMLU), math (GSM8K), code (HumanEval)
- RL the model optionally on GSM8K with "GRPO"
- Efficient inference the model in an Engine with KV cache,...
Перейти на оригинальный пост
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Hugging Face (Twitter)
RT @maximelabonne: New LFM2 release 🥳
It's a Japanese PII extractor with only 350M parameters.
It's extremely fast and on par with GPT-5 (!) in terms of quality.
Check it out, it's available today on @huggingface!
RT @maximelabonne: New LFM2 release 🥳
It's a Japanese PII extractor with only 350M parameters.
It's extremely fast and on par with GPT-5 (!) in terms of quality.
Check it out, it's available today on @huggingface!
Hugging Face (Twitter)
RT @karpathy: @ClementDelangue @huggingface: Ty! huggingface work/infra/datasets are critical to projects like nanochat - to be accurate the source code of nanochat (e.g. at the $100 tier) is ~8KB of Python and ~30GB of fineweb/smoltalk.
RT @karpathy: @ClementDelangue @huggingface: Ty! huggingface work/infra/datasets are critical to projects like nanochat - to be accurate the source code of nanochat (e.g. at the $100 tier) is ~8KB of Python and ~30GB of fineweb/smoltalk.
Hugging Face (Twitter)
RT @vanstriendaniel: @nanonets just shipped Nanonets-OCR2: new 3B VLM for OCR!
LaTeX equations, tables, handwriting, charts, multilingual - it does it all!
You can try it against your data with one command via @huggingface Jobs - no local GPU needed!
The HF Jobs command/output from the model 👇
RT @vanstriendaniel: @nanonets just shipped Nanonets-OCR2: new 3B VLM for OCR!
LaTeX equations, tables, handwriting, charts, multilingual - it does it all!
You can try it against your data with one command via @huggingface Jobs - no local GPU needed!
The HF Jobs command/output from the model 👇
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Hugging Face (Twitter)
RT @NielsRogge: Very cool new document AI release by @barrowjoseph on @huggingface
A free tool to automatically convert PDFs into fillable forms :)
Outperforms @Adobe Acrobat by training open-source models for <$500!
RT @NielsRogge: Very cool new document AI release by @barrowjoseph on @huggingface
A free tool to automatically convert PDFs into fillable forms :)
Outperforms @Adobe Acrobat by training open-source models for <$500!
Hugging Face (Twitter)
RT @ClementDelangue: Am I wrong in sensing a paradigm shift in AI?
Feels like we’re moving from a world obsessed with generalist LLM APIs to one where more and more companies are training, optimizing, and running their own models built on open source (especially smaller, specialized ones)
Some validating signs just in the past few weeks:
- @karpathy released nanochat to train models in just a few lines of code
- @thinkymachines launched a fine-tuning product
- rising popularity of @vllm_project, @sgl_project, @PrimeIntellect, Loras, trl,...
- 1M new repos on HF in the past 90 days (including the first open-source LLMs from @OpenAI)
And now, @nvidia just announced DGX Spark, powerful enough for everyone to fine-tune their own models at home.
Would you agree, or am I just seeing the future I want to exist? Also, why is this happening (just the advent of RL/post-training?)
RT @ClementDelangue: Am I wrong in sensing a paradigm shift in AI?
Feels like we’re moving from a world obsessed with generalist LLM APIs to one where more and more companies are training, optimizing, and running their own models built on open source (especially smaller, specialized ones)
Some validating signs just in the past few weeks:
- @karpathy released nanochat to train models in just a few lines of code
- @thinkymachines launched a fine-tuning product
- rising popularity of @vllm_project, @sgl_project, @PrimeIntellect, Loras, trl,...
- 1M new repos on HF in the past 90 days (including the first open-source LLMs from @OpenAI)
And now, @nvidia just announced DGX Spark, powerful enough for everyone to fine-tune their own models at home.
Would you agree, or am I just seeing the future I want to exist? Also, why is this happening (just the advent of RL/post-training?)