Host Git-based models, datasets and Spaces on the Hugging Face Hub.
State-of-the-art ML for Pytorch, TensorFlow, and JAX.
State-of-the-art diffusion models for image and audio generation in PyTorch.
Access and share datasets for computer vision, audio, and NLP tasks.
Build machine learning demos and other web apps, in just a few lines of Python.
Hub Python Library
Client library for the HF Hub: manage repositories from your Python runtime.
A collection of JS libraries to interact with Hugging Face, with TS types included.
Community library to run pretrained models from Transformers in your browser.
Use more than 50k models through our public inference API, with scalability built-in.
Easily deploy your model to production on dedicated, fully managed infrastructure.
Parameter efficient finetuning methods for large models
Easily train and use PyTorch models with multi-GPU, TPU, mixed-precision.
Fast training and inference of HF Transformers with easy to use hardware optimization tools.
Train and Deploy Transformers & Diffusers with AWS Trainium and AWS Inferentia.
Fast tokenizers, optimized for both research and production.
Evaluate and report model performance easier and more standardized.
All things about ML tasks: demos, use cases, models, datasets, and more!
API to access the contents, metadata and basic statistics of all Hugging Face Hub datasets.
Create and share simulation environments for intelligent agents and synthetic data generation.
Train and Deploy Transformer models with Amazon SageMaker and Hugging Face DLCs.
State-of-the-art computer vision models, layers, optimizers, training/evaluation, and utilities.
Simple, safe way to store and distribute neural networks weights safely and quickly.
AutoTrain API and UI