Ecosystem & Stack: ray

An easy-to-use, scalable, and high-performance open-source framework for Reinforcement Learning from Human Feedback (RLHF), leveraging Ray and vLLM for distributed training of LLMs and VLMs.

A low-code, declarative framework for building and deploying custom large language models (LLMs) and other deep neural networks with ease and efficiency.

A Python library for generating and curating high-quality synthetic data for AI model training and structured data extraction.

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

A high-performance data engine for AI and multimodal workloads, processing diverse data types at scale with Python and Rust.