Llava-v1.5-7B-GGUF
| Property | Value |
|---|---|
| Original Model | liuhaotian/llava-v1.5-7b |
| Context Size | 4096 tokens |
| Quantization Options | Q2_K to Q8_0 |
| Author | second-state |
What is Llava-v1.5-7B-GGUF?
Llava-v1.5-7B-GGUF is a quantized version of the LLaVA (Large Language and Vision Assistant) model, optimized for efficient deployment while maintaining performance. It comes in various GGUF (GGML Universal Format) quantization levels, ranging from 2.53GB to 7.16GB in size.
Implementation Details
The model is implemented using LlamaEdge technology (v0.16.2) and utilizes the vicuna-llava prompt template. It features multiple quantization options to balance between model size and quality, with specific configurations for different use cases.
- Supports various quantization methods (Q2_K to Q8_0)
- Includes multimodal projection model (mmproj)
- Context window of 4096 tokens
- Compatible with LlamaEdge service deployment
Core Capabilities
- Multimodal understanding (text and vision)
- Flexible deployment options with different quantization levels
- Efficient memory usage with GGUF format
- Balanced performance-to-size ratio options
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its range of quantization options, allowing users to choose between extremely compressed versions (Q2_K at 2.53GB) to high-quality variants (Q8_0 at 7.16GB), making it adaptable to various hardware constraints and use cases.
Q: What are the recommended use cases?
The Q4_K_M and Q5_K_M variants are recommended for general use, offering a good balance between quality and size. Q5_K_M (4.78GB) is particularly recommended for applications requiring very low quality loss, while Q4_K_M (4.08GB) provides a balanced approach for most applications.
