Hugging Face

‌Hugging Face (Twitter) RT @RisingSayak: Some notes on what someone can do for building chops in ML x open source x modeling: • Take a popular pre-trained model implementation, profile it, spot the bottlenecks, & try to improve its speed-memory trade-off -- it's a valuable skill that any sane hiring manager should understand and credit (they are probably not legit if they don't). is a good example of this. • GPUs are in short supply. So, try reimplementing it in JAX, leveraging its strengths. Make it run on TPUs, blazing fast 🔥 -- this will help you establish that you care about performance and are comfortable switching stacks when needed. https://github.com/sanchit-gandhi/whisper-jax is an amazing example of this. • In the context of an organization, communication is the key. Make sure you document your experience in an easily digestible way so most folks would understand what you achieved. Provide numbers on benchmarks, mention assumptions, and whatever limitations you faced and how you approached them. • Get a pro subscription to whatever AI coding assistant you think works the best for your stuff. Make it a part of your workflow, but DO NOT become overly reliant on it. Have enough juice in the process so that you can build muscle memory and objective evidence of your intellect over time. • Have fun! It gives me a sense of joy and relief to know that back in the days, we did all of it happily WITHOUT any AI coding assistance. Lots of fun, despair, and anxiety -- but all worth it; 10/10 -- would do it again!

Hugging Face (Twitter) RT @ariG23498: We (/w @RisingSayak) are going to represent @huggingface at the PyTorch Day India event this year. Here is the plan, we go to Bengaluru, talk about Transformers and Kernels, coversate with like minded folks and then leave. Short and sweet! If you are still on the edge of deciding whether to attend or not, we give you another good reason to attend. 🤗 See you there.

‌Hugging Face (Twitter) RT @overworld_ai: If you just want to try it: You can download the model here right now: https://huggingface.co/Overworld/Waypoint-1-Small

Hugging Face (Twitter) RT @evalstate: Open Weights & Open Source v Claude Code. How does [Toad's] fractal on the title page work? Speeded up 4x. Mixture of zai-org/GLM-4.7 and openai/gpt-oss via Hugging Face Inference providers. Join Toad Explorers and get $20 of inference provider credits

Hugging Face (Twitter) RT @staghado: 🚀 LightOnOCR-2-1B 🦉 is out, a major update to LightOnOCR. 1B parameters, end-to-end multilingual OCR, and it beats models 9× larger on OlmOCR-Bench while being much faster. PDF/page in, clean ordered Markdown out, with optional image localization (bbox variants).

Hugging Face (Twitter) RT @novita_labs: 🤗 GLM-4.7-Flash is now live on @huggingface , powered by Novita. Try it yourself 👇

Hugging Face (Twitter) RT @mervenoyann: real-time vision in your browser 🔥 try out YOLO26 for pose estimation and detection built on WebGPU ⚡️

Hugging Face (Twitter) RT @RisingSayak: In case anyone missed -- new models were shipped in Diffusers this week. 1️⃣ Flux.2 Klein - significantly consumer-friendlier than Flux.2 2️⃣ GLM Image - AR + Diffusion Decoder Check'em out!

‌Hugging Face (Twitter) RT @MongoDB: voyage-4-nano is now available. It’s a lightweight, open-weights embedding model designed for fast, cost-efficient retrieval. Available on @huggingface. mongodb.social/6011CLDZL

Hugging Face (Twitter) RT @calebfahlgren: Benchmark Leaderboards seen in the wild on @huggingface👀🏆

Hugging Face (Twitter) RT @lhoestq: Crazy ! 🤯 I was sceptical so I had to check the dataset See for yourself, the truth is here: there are indeed white spaces indicating the true answer in some examples (thanks to the AI assistant on @huggingface for the SQL query) https://twitter.com/fujikanaeda/status/2011565035408277996#m

Hugging Face (Twitter) RT @jack: amazing https://twitter.com/GoogleDeepMind/status/2011848249850630363#m