An Open Source Machine Learning Framework for Everyone

Tensors and Dynamic neural networks in Python with strong GPU acceleration

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

A high-throughput and memory-efficient inference and serving engine for LLMs

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Open standard for machine learning interoperability

ONNX Runtime: cross-platform, high performance ML inferencing and training accelerator

Development repository for the Triton language and compiler

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

State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

Ongoing research training transformer models at scale

Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft

RTAB-Map library and standalone application

Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to …

functorch is JAX-like composable function transforms for PyTorch.

NCCL Tests

⚡ Competitive Programming Library

A Python-level JIT compiler designed to make unmodified PyTorch programs faster.

A deep NLP library, based on Keras / tf, focused on question answering (but useful for other NLP too)

End-to-End recipes for pre-training and fine-tuning BERT using Azure Machine Learning Service

List of resources to get started with Deep Learning for NLP.

Examples for using ONNX Runtime for model training.

A tensorflow implementation of Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks

Graph dump of torchbench models, huggingface models, and TIMM models.