Repository for bittensor validators

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

Merlin Models is a collection of deep learning recommender system model reference implementations

An Engine-Agnostic Deep Learning Framework in Java

Determined: Deep Learning Training Platform

Internet-scale Neural Networks

Machine learning on FPGAs using HLS

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

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a toolkit of libraries (Ray AIR) for accelerating ML workloads.

AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.

A universal scalable machine learning model deployment solution

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.

Boilerplate for PyTorch Lightning based medical-image segmentation pipeline for to enable automated segmentation of organs-at-risk (in head and neck cancer) by using Simple Open-Source 3D CNNS

A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).

A Data Streaming Library for Efficient Neural Network Training

Spatiotemporal datasets collected for network science, deep learning and general machine learning research.

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

Using PyTorch within OpenFOAM

Integrate AI-powered Document Analysis Pipelines

Scalable and user friendly neural :brain: forecasting algorithms.

Unified AI

Stable diffusion headless console and web interface

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

High-performance automatic differentiation of LLVM and MLIR.

Deep learning framework to train, deploy, and ship AI products Lightning fast.

:microscope: Scientific computing library for optics :telescope:, computer graphics :computer: and visual perception :eyes:

Train neural networks up to 7x faster

Enabling PyTorch on XLA Devices (e.g. Google TPU)

AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data

Pytorch/JAX implementation of examples in Generative Deep Learning 2nd Edition by David Foster