Mount Hugging Face Buckets and repos as local filesystems. No download, no copy, no waiting.

Wan: Open and Advanced Large-Scale Video Generative Models

Multilingual Document Layout Parsing in a Single Vision-Language Model

Code accompanying the paper “Fractional Rotation, Full Potential? Investigating Performance and Convergence of Partial RoPE.”

Hundreds of models & providers. One command to find what runs on your hardware.

Parallel rsync-like pull sync over SSH with resume

[ICLR 2025] 🧬 RegMix: Data Mixture as Regression for Language Model Pre-training (Spotlight)

Code for 'Answer Matching Outperforms Multiple Choice for Language Model Evaluation' paper

A framework for efficient model inference with omni-modality models

Call commands safely by checking them rigorously against an allow-list

🎨 NeMo Data Designer: A general library for generating high-quality synthetic data from scratch or based on seed data.

Build compute kernels and load them from the Hub.

A simple, fast and robust program-aware agentic inference system.

Qwen3.5 is the large language model series developed by Qwen team, Alibaba Cloud.

we have ai at home

Every Eval Ever is a shared schema and crowdsourced eval database. It defines a standardized metadata format for storing AI evaluation results — from leaderboard scrapes and research papers to loca…

A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.

Build reliable Gen AI solutions without overhead 🍕

Gets your TFLOPs for your GPU quickly

Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2

Explorations into the proposed SDFT, Self-Distillation Enables Continual Learning, from Shenfeld et al. of MIT

A template for research projects in computer science/machine learning using python and julia

Pytorch Distributed native training library for LLMs/VLMs with OOTB Hugging Face support

Training library for Megatron-based models with bidirectional Hugging Face conversion capability

For releasing code related to compression methods for transformers, accompanying our publications

[ICML 2024] Official Implementation of SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks

Compressed LLMs for Efficient Text Generation [ICLR'24 Workshop]

A CLI to estimate inference memory requirements for Hugging Face models, written in Python.