#pytorch

Training Sparse Autoencoders on Language Models

TritonParse: A Compiler Tracer, Visualizer, and Reproducer for Triton Kernels

docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning. Ongoing development and maintenance by t2k.

Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages

PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.

DeepInverse: a PyTorch library for solving imaging inverse problems using deep learning

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

TorchX is a universal job launcher for PyTorch applications. TorchX is designed to have fast iteration time for training/research and support for E2E production ML pipelines when you're ready.

Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

ncnn is a high-performance neural network inference framework optimized for the mobile platform

Simplify your onnx model

Data manipulation and transformation for audio signal processing, powered by PyTorch

Brevitas: neural network quantization in PyTorch

The fastai deep learning library

optimizer & lr scheduler & loss function collections in PyTorch

Python SDK to interact with the Hopsworks API

Open-source framework for uncertainty and deep learning models in PyTorch 🌱

High-performance automatic differentiation of LLVM and MLIR.

cuDNN Frontend is NVIDIA's modern, open-source entry point to the cuDNN library and a growing collection of high-performance open-source kernels.

A highly efficient implementation of Gaussian Processes in PyTorch

IREE's PyTorch Frontend, based on Torch Dynamo.

A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic workflow for AI agents.

High Performance Computation for N-D Tensors in .NET, similar API to NumPy.

Soup turns the pain of LLM fine-tuning into a simple workflow. One config, one command, done.

Tensor Fusion is a state-of-the-art GPU virtualization and pooling solution designed to optimize GPU cluster utilization to its fullest potential.

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

S2FFT: Differentiable and accelerated spherical transforms

High-performance safetensors model loader