Hugging Face
HuggingFace is the platform where the AI community collaborates on models, datasets, research papers and applications. Let's go open science and open-source!
Channel created: March 20, 2020
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How To Win Humanity's Last Hackathon - The hardest agent contest in AI.
Follow this org to sign up: https://hf-learn.short.gy/nvB8JD The hardest agent contest in AI just launched. Here's how to win it. You can now sign up to Humanity's Last Hackathon. You build Mac Me...
Multi-Agent AutoResearch with Open Source Models
In this video, we walk through a multi-agent setup of AutoResearch using open source models and OpenCode. Timestamps 00:00 - Introduction: Multi-agent AutoResearch setup 01:07 - Agent Roles: Resea...
RL for Agents Workshop - Deep Dive on Training Agents with RL and Open Source
Reinforcement learning is becoming central to agentic systems, but moving from RL for LLMs to RL for agents introduces a new set of challenges: environments, rollouts, tool use, inference bottlenec...
Hugging Face Journal Club: Embarrassingly Simple Self-Distillation Improves Code Generation
The Hugging Face research team discusses Apple's Embarrassingly Simple Self-Distillation Improves Code Generation paper. Paper: https://huggingface.co/papers/2604.01193
RoPE: Understanding Rotary Positional Embeddings in transformers
Mastering Rotary Positional Embeddings (RoPE): From Zero to Deep Dive Unlock the secrets behind modern Large Language Model (LLM) architectures in this comprehensive breakdown of Rotary Positional...
What are Mixture-of-Experts Models | ft. Aritra
In this clip, Aritra Roy Gosthipaty from the Hugging Face Transformers team breaks down one of the most important (and often misunderstood) architectures in modern AI: Mixture-of-Experts models. M...
Intro to Mixture of Experts | Aritra Roy Gosthipaty | HF Podcast #2
In this episode, Alejandro sits down with Aritra Roy Gosthipaty from the Hugging Face Transformers team to talk about mixture-of-experts models, why dense models still matter, how synthetic data ch...
