Repository History

maestro: Streamlining Fine-Tuning for Multimodal Models like PaliGemma 2 and Florence-2

maestro is a powerful tool designed to accelerate the fine-tuning process for multimodal models. It encapsulates best practices, handling configuration, data loading, reproducibility, and training loop setup efficiently. The project currently offers ready-to-use recipes for popular vision-language models, including Florence-2, PaliGemma 2, and Qwen2.5-VL.