🧠 Following Hugging Face's blog on scaling test-time compute with open models—letting models "think longer," inspired by OpenAI & DeepMind—I created a recipe to extend inference time for Instruct LLMs, tackling harder tasks like complex math problems. Links below 👇

I’m a big fan of smol models—compact, efficient, and perfect for inference/training on limited resources. Even better when they’re multimodal! 🤏✨ I explored fine-tuning SmolVLM, a multimodal smol model using TRL with SFT and DPO, creating 2 hands-on projects! 🔗Links below👇

💡I've been exploring how to go smol with multimodal RAG. I've created a project using SmolVLM and ColSmolVLM to create a multimodal RAG that can run on Colab's free tier. Featuring: 🤏👀 SmolVLM (VLM) 🤏📚ColQwen2 (Doc Retrieval) ⚙️ Runs in Colab's free-tier GPU Link below

💡 New Multimodal RAG Recipe with Re-Ranking 💡 I explored how to enhance a multimodal RAG pipeline by integrating a re-ranker! Featuring: ✨ Qwen2-VL-7B (VLM) 📚 ColQwen2 (Doc Retrieval) 🔍 MonoQwen2 (Re-ranking) 🔥 Optimized for consumer GPUs with quantized VLMs. Link below:

Learn how to build a complete multimodal RAG pipeline with ColQwen2 as retriever, MonoQwen2-VL as reranker, Qwen2-VL as VLM in this notebook that runs on a GPU as small as L4 🔥 huggingface.co/learn/cookbo...

✨ Gave a talk on autonomous driving today to undergrad students! We covered everything from definitions to real-world examples, plus cutting-edge concepts like Generative World Models and Vision-Language Models (VLMs). Exciting future ahead! 🚗💡

This is such a cool project, and it was a truly exciting experience to contribute to it!! 😀

Johannes@johko.bsky.social · 2y ago

🌟 500! 🌟 Our Community Computer Vision Course Repo just reached 500 stars on GitHub: github.com/johko/comput... 🤩 I'm really proud of all the amazing content people from the community have contributed here and that they still keep on adding very cool and helpful material 💪

We took those TRL notebooks from last week and made a page from them. So if you're upskilling on finetuning or aligning LLMs, and want examples from the community (like Maxime Labonne Philipp Schmid Sergio Paniego Blanco), check it out! bsky.app/profile/benb... >> huggingface.co/docs/trl/mai...

Community Tutorials

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

huggingface.co

Ben Burtenshaw@benburtenshaw.bsky.social · 2y ago

TRL is a cornerstone of LLM post training and imo it's the default to learn. There are great alternatives like Unsloth, Axolotl, and AutoTrain. But if you want a daily drive that does experimentation to production, it's TRL. 🧵 these community notebooks guide you through TRL's core:

I've been exploring the latest Llama 3.2 releases and working on a couple of projects you may find interesting: 1️⃣ Understanding tool calling with Llama 3.2 🔧 2️⃣ Using Text Generation Inference (TGI) with Llama models 🦙 (links in the next post)

💡 A few days ago, I came across a fascinating post about Agentic RAG by Erika Cardenas and Leonie Monigatti, and it inspired me to dive into the concept and bring it to life in code!

4/6 More vision skills for complex visual tasks. This tutorial shows how to fine-tune the Qwen2-VL-7B model for visual question answering using the ChartQA dataset. huggingface.co/learn/cookbo... by @sergiopaniego.bsky.social

Fine-Tuning a Vision Language Model (Qwen2-VL-7B) with the Hugging Face Ecosystem (TRL) - Hugging Face Open-Source AI Cookbook

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

huggingface.co

TRL is a cornerstone of LLM post training and imo it's the default to learn. There are great alternatives like Unsloth, Axolotl, and AutoTrain. But if you want a daily drive that does experimentation to production, it's TRL. 🧵 these community notebooks guide you through TRL's core:

hola 👋 hi 👋