LLaVA (Large Language and Vision Assistant)

🖼️ Tool name:
LLaVA (Large Language and Vision Assistant)

🔖 Tool Category:
A multimodal AI model; falls under the category of large open-source multimodal models (LMMs) that combine image understanding and language generation for video chat and question answering.

✏️ What does this tool offer?
LLaVA is a large open-source open-source multimodal model that combines a visual encoder (CLIP ViT-L) with a powerful language model (e.g. Vicuna) to enable advanced image-to-text reasoning. It allows users to input images, ask questions about them, and generate intelligent responses. LLaVA supports visual captioning, image annotation, visual reasoning, and multimodal conversational AI.

⭐ What does the tool actually do based on user experience?
- Handles complex visual inputs and generates accurate, human-like responses
- Strong performance in visual QA benchmarks, reaching approximately 85% of GPT-4V's performance
- Supports high-resolution image input, optical character recognition (OCR) reading, and chart/table understanding
- Available in lightweight versions (e.g., LLaVA-Lightning) for rapid training and low-cost deployment
- Well documented and easy to run locally via the Gradio demo
- Popular among researchers, developers, and the open source AI community

🤖 Does it include automation?
Yes - LLaVA includes automation in:
- Automatic generation of multimodal training data using GPT-4 to adjust visual instructions
- Model-assisted annotation and vision-to-language alignment
- Rapid training using tools like LLaVA-Lightning (training in hours with minimal resources)
- Automatic inference and generation of visual prompts without manual intervention

💰 Pricing model:
Free and open source

🆓 Free plan details:
- Fully open source with MIT license
- Available to download and run locally
- Pre-trained templates hosted on Hugging Face
- No usage limits; local or cloud hosting costs depend on user setup

🧭 Method of access:
- Run locally via Python and Gradio interface
- Clone from GitHub: https://github.com/haotian-liu/LLaVA
- Download pre-trained models from Hugging Face or the Zoo model
- Demo available through the browser interface (no login required)

🔗 Link to the demo:
- Official demo: https://llava.hliu.cc