Tags: #foundation-models

A comprehensive research hub for large-scale self-supervised pre-training of foundation models across diverse tasks, languages, and modalities.

Autodistill automates the process of training small, fast supervised models from unlabeled images by leveraging large foundation models, eliminating the need for manual data labeling.

A PyTorch library providing advanced foundation architectures to efficiently and effectively scale Transformers for large language models and general-purpose AI.