Individual skill

blip-2-vision-language

Explains how to use Salesforce BLIP-2 (Q-Former bridging a frozen image encoder and an LLM such as OPT or FlanT5) through HuggingFace Transformers and LAVIS for image captioning, visual question answering, image-text matching, and feature extraction. Use when generating captions for images, building a VQA system, doing zero-shot image-text understanding without task-specific training, matching or retrieving images against text, or fitting a BLIP-2 model into limited GPU memory with INT8/INT4 quantization. Prefer LLaVA or InstructBLIP for instruction-following multimodal chat, and CLIP for plain image-text similarity.

plugins/KalarisLabs/research-agent-skills/skills/blip-2-vision-language/SKILL.md

Source commit d780783eba4ecc7c8b9429f95c9362df95f07c61

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Last checked

Nov 4, 2026

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