Knowledge catalogue
Local models do seem likely to create an explosion of new use cases. Local compute >> cloud compute. This is where we are right now. And i’m not gonna lie it feels pretty magical 🧚♀️ Qwen3.6 27B runn
🚀Meet Carnice-V2-27b🚀 → Carnice is a 27 billion parameter model capable of beating models 10x the size in Hermes-agent, fully open-source and built on top of Qwen3.6-27B →Build to fit on Consumer GPU
A new Dflash drafting model based on Qwen 3.6 with 27 billion parameters has been released on Hugging Face, available at z-lab/Qwen3.6-27B-DFlash. This model likely implements speculative decoding or
OpenAI just released HealthBench Professional on Hugging Face A medical evaluation benchmark designed to improve AI assistants for clinicians, featuring physician-curated conversations and rubric-base
This post discusses the need for built-in speech-to-text (STT) and text-to-speech (TTS) capabilities in a product or platform (likely referring to Hugging Face's platform based on the mention of Clem
Spot on 🎯 We don't need frontier intelligence to automate searches and sending emails - We don't need trillion parameter models to be able to summarize articles or technical documents - We don't need
Clem Delangue expressed his personal motivation for continuing work in the open-source space, stating that enjoyment is his primary driver for persisting in the field. He also expressed confidence tha
We built HF for AI builders collaboration, fun to see it's increasingly becoming the place for agent collaboration! This morning I'm sending my ml-intern to participate in the @OpenAI Parameter Golf c
We've got all the models here: https://dell.huggingface.co/authenticated/models Kimi K2.5, Mistral, Cohere, Arcee AI Trinity Large, Google Gemma, Meta/Llama, Qwen, Nvidia Nemotron, Grok, GPT OSS, Deep
DeepSeek-V4 rapidly gained over 500 likes within 28 minutes on Hugging Face, demonstrating exceptional user engagement and positioning it as a strong contender to become the fastest model to reach #1
And the more distributed and open-source AI will be, the more jobs and wealth it will create! I have changed my mind on how AI will impact jobs in America. Previously, I believed AI would replace many
🚨BREAKING: Hugging Face just open-sourced an AI intern that reads ML papers, trains models, and ships the final model for you. It’s called ML Intern. And this is not another AI coding demo that prints
Cloud-hosted models will become more niche/seldom-used as much cheaper local models fulfill that which 90% of consumers need from AI. Lots of models to buy/use, but very few hardware options upon whic
Clem Delangue from Hugging Face announced upcoming machine learning research from Shopify, though specific details about the research topic or findings are not provided in this teaser post. The post s
DeepSeek-V4 is a newly released AI model announced by Clem Delangue on X (formerly Twitter). The release likely represents an updated version of the DeepSeek model series with improvements in capabili
DeepSeek has released v4, its latest model iteration. The announcement was made by Clem Delangue on X (formerly Twitter). This likely represents a significant update to DeepSeek's AI capabilities, tho
DeepSeek-V4, a new model release from DeepSeek AI, has been made available on Hugging Face's model hub. The release was announced by Clem Delangue and includes model weights and resources accessible t
For the last 72 hours since ml-intern launched we have had over 500+ autonomous AI research projects running on the Space at all times. Some insane ones I saw: 1. A new AI paradigm from scratch — tryi
Hugging Face offers a $9 Pro account subscription that provides significant value compared to other developer tool subscriptions. According to Clem Delangue, CEO of Hugging Face, this pricing tier rep
DeepSeek-V4 is a collection of models released by DeepSeek-AI on Hugging Face that represents their latest generation of large language models. The collection likely includes various model sizes and c
Clem Delangue highlights a significant development in local inference technology, noting that a project (referred to as 'whale bros') has released their work as open source. The post emphasizes the im
If you forget about the Harveys and Lovables and Anthropics for a second … getting to 100M in revenue is very rare. According to this dataset ca. 1.5% of VC funded startups. If you’ve achieved that as
I'm always baffled how most investors seem to obsess over top revenue growth numbers these days and seem to take that as a universal prediction of future success in AI. Maybe we're finally starting to
Clem Delangue posted about someone flying to work with the llama.cpp team on developing next-generation local AI capabilities, framed as meta commentary on headlines related to the endeavor. The post
pi gives you wings wherever you are This is where we are right now. And i’m not gonna lie it feels pretty magical 🧚♀️ Qwen3.6 27B running inside of Pi coding agent via Llama.cpp on the MacBook Pro Fo
【Qwen-3.6-27B × llama.cpp】生成速度10倍の革命的スピード！ Qwen-3.6-27Bで生成速度が約10倍の136.75 t/sに到達する驚異の手法が話題です！🚀 llama.cppの「ngram-mod」という投機的デコード（Speculative Decoding）を活用。過去の出力パターンを利用して次に来る言葉を予測し、追加のビデオメモリをほぼ消費せずに高速化を実現し
sorry everyone, we're working on being able to allow more concurrent workloads! Was about to take a jab at understanding CSA and HCA with ML-intern at Hugging Face, @huggingface please upgrade the int
DeepSeek V4 Pro is a new AI model release from Chinese AI company DeepSeek, announced via Hugging Face. The post expresses enthusiasm about the model's capabilities and performance, suggesting it repr
This is where we are right now. And i’m not gonna lie it feels pretty magical 🧚♀️ Qwen3.6 27B running inside of Pi coding agent via Llama.cpp on the MacBook Pro For non-trivial tasks on the @huggingf
DeepSeek V4 Pro Max is a large language model released by DeepSeek AI and made available on Hugging Face, representing an advancement in their model lineup. The announcement was made by Clem Delangue,
A post by Clem Delangue on X documenting a whale sighting, likely sharing an observation or encounter with whales, possibly including location details, images, or commentary about the experience. With
Hugging Face's ml-intern project has reached a testing milestone with 3,000 people actively participating in its evaluation. This suggests significant community interest in what is likely an open-sour
5B tokens in ml-intern in 48h 😅😅😅 we burned through 5 billion tokens in 48h. turns out giving everyone unlimited access to the most expensive model on the planet is not a great business strategy 🙈 So
GPT-5.5 is likely the best model in the world. But open models like Kimi and Minimax get almost identical coding benchmark scores at 10-25x lower cost. I broke down the benchmarks and pricing. Here's
Hugging Face's CEO Clem Delangue expressed optimism about the impact of the company's machine learning internship program, suggesting it will grow significantly in scale or influence. The post indicat
If you can’t stop small teams from using your API for distillation, then you’re definitely not stopping criminals, biohackers, or adversarial states from using AI through it. Those actors are much mor
Mozilla says Mythos helped identify 271 vulnerabilities in Firefox 150. I went through the commits, CVEs, and bug links to see what that number really means. My takeaway: relax folks. https://xark.es/
OpenResearcher is an open-source AI agent designed to conduct long-horizon deep research tasks, enabling autonomous investigation and analysis across extended research workflows. The project is mainta
Opus 4.7 just wrote a custom WebGPU kernel that runs Qwen3.5 up to 13x faster using a fused LinearAttention op! 🤯 Agentic kernel optimization is the future. Now live in 🤗 Transformers.js v4.2.0! P.S.
This post demonstrates a DFlash implementation integrated with llama-cpp, showcasing a speculative decoding setup that uses Qwen 3.6-27B as the main model with a smaller draft model (dflash-draft-q4_k
So right now basically anyone with a 16GB VRAM card can go on @huggingface and download a model which BEATS Claude Sonnet 4.5, all running locally 🤯 LOOK AT THE WATER PARTICLES?? What are they doing i
This is crazy. ml-intern just passed the @huggingface internship test in 15 minutes. The task: replicate a research baseline from a DeepMind paper on test-time compute scaling. Here's what the agent d
Three shifts in the AI stack today: - OpenAI ships GPT-5.5 as a mid-cycle drop before its IPO - Hugging Face's ML Intern beats Claude Code and Codex on research - Pliny used Claude Opus 4.7 to jailbre
we burned through 5 billion tokens in 48h. turns out giving everyone unlimited access to the most expensive model on the planet is not a great business strategy 🙈 So now we have 2 free opus sessions/d
Hugging Face and AMD have collaborated to quantize the Kimi-K2.6 model to MXFP4 format, enabling efficient inference on AMD hardware. MXFP4 is a low-precision floating-point quantization technique tha
🚨 Are we witnessing the automation of AI research? @HuggingFace just unveiled 'ML-Intern' and my mind is BLOWN 🤯 It’s an open-source pipeline that replicates the exact daily loop of an ML researcher.
Guys, I am absolutely astounded. The Qwen 3.6 27b is like a jump to Qwen 4 from Qwen 27B 3.5. I just did a full suite of front end design tests and agentic benchmarks, made entirely by it. VERDICT: Th
Hugging Face Releases ml-intern: An Open-Source AI Agent that Automates the LLM Post-Training Workflow [The 'AI Intern' that actually ships SOTA models ] This isn't just another ML Research Loop wrapp
Clem Delangue, CEO of Hugging Face, shared a post about post-training a model using ml-intern, likely referring to a machine learning internship project or internal tool. The post appears to be a casu
This post likely demonstrates running Qwen2 3.6B or 27B model in GGUF format using llama-server with default specifications, showcasing inference capabilities of quantized open-source models. The comm
ml-intern by @huggingface is wild 🔥 You drop a high-level prompt (“build the best scientific reasoning model” or “crush healthcare benchmarks”) and this open-source agent does the entire post-training
Clem Delangue, co-founder of Hugging Face, shared an encouraging observation about an ML intern who is facing challenges in their work but persisting through difficulties. The post uses celebratory em
OpenAI released a new model that was made available on Hugging Face, as announced by Hugging Face CEO Clem Delangue on X (formerly Twitter). The specific details about which model was released are not
OpenAI just open sourced a new 1.5B (50m active) model on HuggingFace with Apache 2.0 license! It's not a new LLM, this one is called Privacy Filter, and it's a PII detection model (checking if text h
OpenAI just released a new open-source model it's 'a bidirectional token-classification model for personally identifiable information (PII) detection and masking in text' https://github.com/openai/pri
This post from Hugging Face CEO Clem Delangue discusses the value of persistence in machine learning work, using an anecdote about observing an intern working through problems. The tweet emphasizes th
Qwen3.6-27B-TQ3_4S is a quantized 27 billion parameter language model that fits on 16GB of VRAM while supporting a 32k token context window, demonstrating strong performance across tested prompts. The
Qwen3.6-35B-A3B has achieved #1 trending status on Hugging Face, indicating significant community interest and adoption of this large language model. The announcement highlights the model's popularity
Qwen3.6 and gemma 4 just shown that we were still far from capability limit on small models, we still are. Huge models are good, but is there really a point in going bigger. Just realize something. On
Read THIS by @huggingface’s @ClementDelangue, @YJernite and @mmitchell_ai “Openness provides defenders with the visibility, the control, the community, and the shared infrastructure to stay ahead.” ht