Answer questions about images using a multimodal vision-language model.
npx skills add https://github.com/ricable/mcai --skill llava-ricable
Please help me install this Agent Skill. Skill: llava Source: https://github.com/ricable/mcai/tree/main/.agents/skills/llava Command: npx skills add https://github.com/ricable/mcai --skill llava-ricable
LLaVA helps people ask natural-language questions about images and receive detailed, context-aware answers without manual visual inspection.
Use the llava skill to analyze an attached image and answer a user question about what is visible in it.
High-intent search queries and answers about installing and using this skill.
Visual question answering uses a multimodal vision-language model to generate context-aware answers about images. You attach an image and ask a natural-language question to receive detailed responses without manual inspection.
Yes, a vision-language model supports multi-turn image chat and document image interpretation. It processes image token formatting to handle conversational context and extract text from document images.
Multimodal generation works by routing images through a CLIP-based vision encoder and text through a LLaMA language model. The encoded visual features merge with language tokens for unified vision-language reasoning.
Fine-tuning support is optional for building multimodal chatbots. You can use base models for general scene understanding, but fine-tuning improves accuracy for domain-specific visual analysis workflows.
Quantization reduces memory usage during image captioning but may degrade output precision. Optional quantization support helps deploy multimodal vision-language models in resource-constrained environments.
HarriesCombine a CLIP vision encoder with Vicuna or LLaMA for image-based chat and visual question answering.
zerwizAnswer visual questions and caption images through conversational prompts.
ovachieverAutomate LLaMA-family model fine-tuning via the Llama-Factory WebUI.
vuminhieuDesign unified multimodal prompts for audio, image, and video tasks across Gemini, Imagen, and Veo.
