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Tensors and Dynamic neural networks in Python with strong GPU acceleration
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The world's simplest facial recognition api for Python and the command line
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, i…
OpenMMLab Detection Toolbox and Benchmark
Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Graph Neural Network Library for PyTorch
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
Datasets, Transforms and Models specific to Computer Vision
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
End-to-End Object Detection with Transformers
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Python Implementation of Reinforcement Learning: An Introduction
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Python package built to ease deep learning on graph, on top of existing DL frameworks.
An open source implementation of CLIP.
PyTorch package for the discrete VAE used for DALL·E.
A PyTorch implementation of the Transformer model in "Attention is All You Need".
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
Matplotlib styles for scientific plotting