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

Fast Inference Solutions for BLOOM

Tensors and Dynamic neural networks in Python with strong GPU acceleration

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

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

Official community-driven Azure Machine Learning examples, tested with GitHub Actions

Docker containers for running training scripts on AzureML

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

Example models using DeepSpeed

Optimized primitives for collective multi-GPU communication

Computation using data flow graphs for scalable machine learning

Example notebooks that show how to apply machine learning and deep learning in Amazon SageMaker

Caffe: a fast open framework for deep learning.

Files to create the figures in the paper "Super-Convergence: Very Fast Training of Residual Networks Using Large Learning Rates"

This fork of BVLC/Caffe is dedicated to improving performance of this deep learning framework when running on CPU, in particular Intel® Xeon processors (HSW+) and Intel® Xeon Phi processors