blip-2-vision-language
BLIP-2: Vision-Language Pre-training
Comprehensive guide to using Salesforce's BLIP-2 for vision-language tasks with frozen image encoders and large language models.
When to use BLIP-2
Use BLIP-2 when:
- Need high-quality image captioning with natural descriptions
- Building visual question answering (VQA) systems
- Require zero-shot image-text understanding without task-specific training
- Want to leverage LLM reasoning for visual tasks
- Building multimodal conversational AI
- Need image-text retrieval or matching
Key features:
- Q-Former architecture: Lightweight query transformer bridges vision and language
- Frozen backbone efficiency: No need to fine-tune large vision/language models
- Multiple LLM backends: OPT (2.7B, 6.7B) and FlanT5 (XL, XXL)
- Zero-shot capabilities: Strong performance without task-specific training
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