T2Vid: Efficient Video Fine-tuning Scheme for MLLMs

   📑 Paper    |    🤗 Hugging Face  

TL;DR: We proposed a data augmentation method (synthesizing "video" samples from long QA text data) to enrich the instruction diversity of video data, which facilitates more efficient training with comparable performance.

🚨 Note

This repo has been moved to a new link.