🤗 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.
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We write your reusable computer vision tools. 💜
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
deep learning for image processing including classification and object-detection etc.
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.
pix2tex: Using a ViT to convert images of equations into LaTeX code.
A very simple framework for state-of-the-art Natural Language Processing (NLP)
🐍 Geometric Computer Vision Library for Spatial AI
A PyTorch-based Speech Toolkit
Low-code framework for building custom LLMs, neural networks, and other AI models
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Fast and Accurate ML in 3 Lines of Code
AI Toolkit for Healthcare Imaging
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
A highly efficient implementation of Gaussian Processes in PyTorch
Accelerated deep learning R&D
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
Data manipulation and transformation for audio signal processing, powered by PyTorch
Multilingual Automatic Speech Recognition with word-level timestamps and confidence
A deep learning toolkit for healthcare AI: EHR (MIMIC, eICU, OMOP), clinical text, signals and imaging. 30+ models, reproducible pipelines.
Audio processing by using pytorch 1D convolution network
Pretrained model hub for Keras 3.