AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

Your CLI home video recorder 📼

SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]

A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)

Ongoing research training transformer models at scale

Hydra is a framework for elegantly configuring complex applications

cuDF - GPU DataFrame Library

An Easy-to-use, Scalable and High-performance Agentic RL Framework based on Ray (PPO & DAPO & REINFORCE++ & TIS & vLLM & Ray & Async RL)

A Datacenter Scale Distributed Inference Serving Framework

NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.

cuML - RAPIDS Machine Learning Library

A high performance and generic framework for distributed DNN training

A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit and 4-bit floating point (FP8 and FP4) precision on Hopper, Ada and Blackwell GPUs, to provide better performance…

cuGraph - RAPIDS Graph Analytics Library

Toolbox of models, callbacks, and datasets for AI/ML researchers.

Scalable data pre processing and curation toolkit for LLMs

PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own.

Scalable toolkit for efficient model reinforcement

A project to improve skills of large language models

BioNeMo Framework: For building and adapting AI models in drug discovery at scale

Speed up model training by fixing data loading.

RAPIDS Sample Notebooks

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

Provides end-to-end model development pipelines for LLMs and Multimodal models that can be launched on-prem or cloud-native.

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