llava Skill
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best Published by NousResearch in hermes-agent.
What is llava Skill?
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best Published by NousResearch in hermes-agent. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Design and media
- Research
- Design and media use cases
- Research use cases
Technical details
- Install or run with Copy skill directory
When to use llava Skill
- Use it for design and media.
- Use it for research.
Built with
Editorial notes
Source
- Creator: NousResearch
- Repository: NousResearch/hermes-agent
- Skill file: optional-skills/mlops/llava/SKILL.md
What it does
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best
Skill instructions
LLaVA - Large Language and Vision Assistant Open-source vision-language model for conversational image understanding. When to use LLaVA Use when: - Building vision-language chatbots - Visual question answering (VQA) - Image description and captioning - Multi-turn image conversations - Visual instruction following - Document understanding with images Metrics: - 23,000+ GitHub stars - GPT-4V level capabilities (targeted) - Apache 2.0 License - Multiple model sizes (7B-34B params) Use alternatives instead: - GPT-4V: Highest quality, API-based - CLIP: Simple zero-shot classification - BLIP-2: Better for captioning only - Flamingo: Research, not open-source Quick start Installation bash Clone repository git clone https://github.com/haotian-liu/LLaVA cd LLaVA Install pip install -e . Basic usage python from llava.model.builder import loadpretrainedmodel from llava.mmutils import getmodelnamefrompath, processimages, tokenizerimagetoken from llava.constants import IMAGETOKENINDEX, DEFAULTIMAGE
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Frequently asked questions
What is llava?
llava is a open-source AI agent skill with Copy skill directory. Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models.
Who is llava best for?
llava is best for reusing agent instructions, scripts, and references, design and media workflows, research workflows.
How do I install llava?
Install or run llava using Copy skill directory. Check llava for the latest setup command.
Is llava actively maintained?
llava may need a closer maintenance check before production use.
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