interpret-community 0.31.0

Client library to download and publish models, datasets and other repos on the huggingface.co hub

Horovod is a powerful distributed training framework for Python that allows you to train deep learning models across multiple GPUs and servers quickly and efficiently. It falls under the category of distributed computing libraries. Built on top of TensorFlow, PyTorch, and other popular deep learning frameworks, Horovod simplifies the process of scaling up your model training by handling the complexities of distributed training under the hood.

Probabilistic time series modeling in Python.

fastai simplifies training fast and accurate neural nets using modern best practices

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

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.

HuggingFace community-driven open-source library of datasets

Fast and Accurate ML in 3 Lines of Code

Text utilities and datasets for PyTorch