🤗 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.

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Models and examples built with TensorFlow

Deep Learning for humans

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

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

Official inference repo for FLUX.1 models

Image-to-Image Translation in PyTorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities

This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

🐍 Geometric Computer Vision Library for Spatial AI

A framework for training and evaluating AI models on a variety of openly available dialogue datasets.

Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

Real-Time and Accurate Full-Body Multi-Person Pose Estimation&Tracking System

PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

Pytorch implementation of convolutional neural network visualization techniques

PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

Deep Learning and Reinforcement Learning Library for Scientists and Engineers

Code release for ConvNeXt model

Simple Online Realtime Tracking with a Deep Association Metric

Image augmentation library in Python for machine learning.

Torchreid: Deep learning person re-identification in PyTorch.

[NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"

High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.

Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference

LightGlue: Local Feature Matching at Light Speed (ICCV 2023)