fastai 2.8.7

DeepSpeed is a Python package developed by Microsoft that provides a deep learning optimization library designed to scale across multiple GPUs and servers. It is capable of training models with billions or even trillions of parameters, achieving excellent system throughput and efficiently scaling to thousands of GPUs.

DeepSpeed is particularly useful for training and inference of large language models, and it falls under the category of Machine Learning Frameworks and Libraries. It is designed to work with PyTorch and offers system innovations such as Zero Redundancy Optimizer (ZeRO), 3D parallelism, and model-parallelism to enable efficient training of large models.

End-to-End Multi-Lingual Optical Character Recognition (OCR) Solution

HuggingFace community-driven open-source library of datasets

ClearML Agent - Auto-Magical DevOps for Deep Learning

Fast and Accurate ML in 3 Lines of Code

Text utilities and datasets for PyTorch

Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

A refreshing functional take on deep learning, compatible with your favorite libraries

HuggingFace/NLP is an open library of NLP datasets.