Vision Language Models Explained

Hugging Face Blog · 2 years ago

Vision language models are multimodal systems that learn from images and text simultaneously to perform tasks like visual question answering, image captioning, and document understanding. The Open VLM Leaderboard and Vision Arena provide benchmarking tools, with MMMU containing 11.5K multimodal challenges requiring college-level reasoning across disciplines. Users can now fine-tune these models using TRL's SFTTrainer with datasets like llava-instruct-mix-vsft, which contains 260K image-conversation pairs.