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

12 Weeks, 24 Lessons, AI for All!

💫 Industrial-strength Natural Language Processing (NLP) in Python

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

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

Open standard for machine learning interoperability

Machine Learning Systems

🐍 Geometric Computer Vision Library for Spatial AI

Swap GPT for any LLM by changing a single line of code. Xinference lets you run open-source, speech, and multimodal models on cloud, on-prem, or your laptop — all through one unified, production-ready inference API.

🧙 Build, run, and manage data pipelines for integrating and transforming data.

An open source cybersecurity protocol for syncing decentralized graph data.

Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages

🤗 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.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image