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Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

Tensors and Dynamic neural networks in Python with strong GPU acceleration

You like pytorch? You like micrograd? You love tinygrad! ❤️

🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.

:bouncing_ball_person: Pytorch ReID: A tiny, friendly, strong pytorch implement of person re-id / vehicle re-id baseline. Tutorial 👉https://github.com/layumi/Person_reID_baseline_pytorch/tree/master/tutorial

🚀 Pytorch Distributed native training library for LLMs/VLMs with OOTB Hugging Face support

Ultralytics YOLOv5 in PyTorch > ONNX > CoreML > TFLite

Datasets, Transforms and Models specific to Computer Vision

Graph Neural Network Library for PyTorch

Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

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

On-device AI across mobile, embedded and edge for PyTorch

TPU inference for vLLM, with unified JAX and PyTorch support.

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..

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

A repository for storing models that have been inter-converted between various frameworks. Supported frameworks are TensorFlow, PyTorch, ONNX, OpenVINO, TFJS, TFTRT, TensorFlowLite (Float32/16/INT8), EdgeTPU, CoreML.

Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learn...

Fine-tune Gemma 4 and 3n with audio, images and text on Apple Silicon, using PyTorch and Metal Performance Shaders.

CnSTD: 基于 PyTorch/MXNet 的 中文/英文 场景文字检测（Scene Text Detection）、数学公式检测（Mathematical Formula Detection, MFD）、篇章分析（Layout Analysis）的Python3 包

PyTorch tutorials.

BigDL: Distributed TensorFlow, Keras and PyTorch on Apache Spark/Flink & Ray

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

A highly efficient implementation of Gaussian Processes in PyTorch

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

邱锡鹏《神经网络与深度学习：案例与实践》PyTorch 实现

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

A simplified framework and utilities for PyTorch

PyTorch Extension Library of Optimized Graph Cluster Algorithms

Pytorch implementation of preconditioned stochastic gradient descent (Kron and affine preconditioner, low-rank approximation preconditioner and more)