Tags: #distributed-training

Streamlines complex deep learning engineering, enabling scalable AI model training and finetuning across diverse hardware with minimal code changes.

An open-source, cloud-native, all-in-one MLOps platform designed for the full lifecycle management of machine learning, deep learning, and large language model development and deployment.

An open-source framework designed to make large AI model training and inference cheaper, faster, and more accessible through advanced distributed computing and memory optimization techniques.

An efficient and user-friendly scaling library designed to optimize Reinforcement Learning with Large Language Models, enhancing performance in complex AI tasks.