Hugging Face

Hugging Face (Twitter) RT @abidlabs: Trackio will soon support Images in Tables. What other features do you need? https://github.com/gradio-app/trackio/pull/328

Hugging Face (Twitter) RT @Gradio: 🎂 MCP turns 1 on Nov 25 We're throwing it the biggest birthday party in AI history @AnthropicAI + Gradio are bringing together thousands of developers for 17 days of building MCP servers and Agentic apps $500K+ free credits for participants. $17.5K+ in cash prizes. Nov 14-30

Hugging Face (Twitter) RT @ClementDelangue: No excuse anymore not to train your own models! This 200+ pages with full transparency. Let's go open-source AI! https://twitter.com/eliebakouch/status/1983930328751153159#m

Hugging Face (Twitter) RT @andimarafioti: We grew up with gaming consoles. Our kids will grow up with robots. Fucking incredible.

Hugging Face (Twitter) RT @Thom_Wolf: Monday morning read: a fascinating deep dive in recent Chinese chips developments as well as the coming co-evolution with LLM builders fresh analysis from the HF team => https://huggingface.co/blog/huggingface/shifting-compute-landscape

Hugging Face (Twitter) RT @angrypenguinPNG: Open-source might have just caught up to NanoBanana dx8152 trained a Qwen Edit LoRA that nails multi-angle shots. Here’s a product video I made using it with Kling Start/End frames. Link to LoRA below 👇

Hugging Face (Twitter) RT @LucSGeorges: times flies when you’re having fun 🫨

Hugging Face (Twitter) RT @_xjdr: What an incredible resource. Anyone interested in pretrainig should read this carefully https://twitter.com/eliebakouch/status/1983930328751153159#m

Hugging Face (Twitter) RT @TheAhmadOsman: yesterday, Hugging Face dropped a 214-page MASTERCLASS on how to train LLMs > it’s called The Smol Training Playbook > and if want to learn how to train LLMs, > this GIFT is for you > this training bible walks you through the ENTIRE pipeline > covers every concept that matters from why you train, > to what you train, to how you actually pull it off > from pre-training, to mid-training, to post-training > it turns vague buzzwords into step-by-step decisions > architecture, tokenization, data strategy, and infra > highlights the real-world gotchas > instabilities, scaling headaches, debugging nightmares > distills lessons from building actual > state-of-the-art LLMs, not just toy models how modern transformer models are actually built > tokenization: the secret foundation of every LLM > tokenizer fundamentals > vocabulary size > byte pair encoding > custom vs existing tokenizers > all the modern attention mechanisms are here >... Перейти на оригинальный пост

Hugging Face (Twitter) RT @yacinelearning: I quit my job so I can have enough time to read this book btw https://twitter.com/eliebakouch/status/1983930328751153159#m

Hugging Face (Twitter) RT @ludwigABAP: if @huggingface released a mega book with all 4 massive essays they wrote on training LLMs (ultra scale playbook, eval guidebook, smol training playbook), I’d buy it for an exorbitant amount just because it’s the closest to what most of us have been interested in and/or doing for the last few years

Hugging Face (Twitter) RT @ahadj0: finally got around to implementing the software for teleoping the detachable gripper on top of @LeRobotHF going to release open source files for it soon