Individual skill
multimodal-blip-2
Vision-language pre-training framework bridging frozen image encoders and LLMs. Use when you need image captioning, visual question answering, image-text retrieval, or multimodal chat with state-of-the-art zero-shot performance.
cli-tool/components/skills/ai-research/multimodal-blip-2/SKILL.md
Source commit ad81bf053f80b626801decf425f501ba49983d98
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Network or broad shell
- Last checked
- Nov 9, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 33,235
- Repository last updated
- Nov 9, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- anthropic Repository topic
- anthropic-claude Repository topic
- claude Repository topic
- claude-code Repository topic
- agent-skills Repository topic
- ai-agents Repository topic
- claude-code-plugins Repository topic
- cli Repository topic
- mcp Repository topic
- registry Repository topic
- multimodal Declared skill tag
- vision-language Declared skill tag
- image-captioning Declared skill tag
- vqa Declared skill tag
- zero-shot Declared skill tag
- design Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
SKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesSKILL.mdcore · 18,629 bytesreferences/advanced-usage.mddoc · 18,889 bytesreferences/troubleshooting.mddoc · 11,981 bytes
Read excerpt
# 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
