petastorm 0.13.1

Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML. It defines an extensible computation graph model, as well as definitions of built-in operators and standard data types. Currently we focus on the capabilities needed for inferencing (scoring).

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.

HuggingFace community-driven open-source library of datasets

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.

Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. The core data structures of Keras are layers and models. The philosophy is to keep simple things simple, while allowing the user to be fully in control when they need to (the ultimate control being the easy extensibility of the source code via subclassing).

Open3D: A Modern Library for 3D Data Processing.

Open Source Differentiable Computer Vision Library for PyTorch