BLIP-2

Zero-shot image-to-text generation with BLIP-2

Hugging Face published a blog post introducing BLIP-2, a multimodal model that enables zero-shot image-to-text generation by bridging frozen image encoders and large language models via a lightweight Querying Transformer (Q-Former). The post covers the model's architecture, capabilities, and how to use it via the Hugging Face Transformers library. BLIP-2 achieves strong performance on visual question answering and image captioning tasks without task-specific fine-tuning.