The open source research environment for AI researchers to seamlessly train, evaluate, and scale models from local hardware to GPU clusters.

Reproducibility package for paper "Round-to-Nearest Is Hard to Beat: A 30B MoE Coding Model in 24 GB on Apple Silicon"

Galleries for Models, Datasets, and Plugins used by Transformer Lab

This is a comprehensive guide that offers advice for how to build a machine learning cluster for researchers at different scales

Python SDK for interacting with Transformer Lab

API Server for Transformer Lab