LLaVA v1.5 7B Llamafile
| Property | Value |
|---|---|
| Parameter Count | 6.74B |
| License | LLAMA 2 Community License |
| Release Date | September 2023 |
| Format | GGUF/Llamafile |
| Project Website | llava-vl.github.io |
What is llava-v1.5-7b-llamafile?
LLaVA (Large Language and Vision Assistant) is a sophisticated multimodal AI model that combines vision and language capabilities. Built on the LLaMA architecture, this 6.74B parameter model represents a significant advancement in multimodal AI, capable of understanding and processing both images and text inputs seamlessly.
Implementation Details
The model is implemented as an auto-regressive transformer architecture, fine-tuned on LLaMA/Vicuna using a carefully curated dataset. The training data encompasses 558K filtered image-text pairs, 158K GPT-generated instructions, 450K academic VQA data, and 40K ShareGPT conversations.
- Multimodal architecture based on transformer technology
- GGUF format optimization for efficient deployment
- Comprehensive training on diverse datasets
- Built-in support for vision-language tasks
Core Capabilities
- Image and text understanding
- Visual question answering
- Multimodal instruction following
- Academic task processing
- Natural language interaction
Frequently Asked Questions
Q: What makes this model unique?
LLaVA stands out for its ability to process both visual and textual information in a unified framework, making it particularly valuable for research and real-world applications requiring multimodal understanding.
Q: What are the recommended use cases?
The model is primarily intended for research purposes in computer vision, natural language processing, and AI. It's particularly suited for researchers and hobbyists working on multimodal AI applications, visual question answering, and advanced chatbot development.
