MFANNv0.25-GGUF
| Property | Value |
|---|---|
| Parameter Count | 8.03B |
| License | LLaMA 3.1 |
| Author | mradermacher |
| Base Model | netcat420/MFANNv0.25 |
What is MFANNv0.25-GGUF?
MFANNv0.25-GGUF is a quantized version of the original MFANNv0.25 model, specifically optimized for efficient inference using the GGUF format. This model provides multiple quantization options to balance between model size, speed, and quality, ranging from 3.3GB to 16.2GB in file size.
Implementation Details
The model offers various quantization types, each serving different use-cases:
- Q2_K to Q8_0 quantization options available
- IQ4_XS offering balanced performance
- F16 format for maximum precision
- Specialized versions like Q4_K_S and Q4_K_M recommended for fast inference
Core Capabilities
- Efficient inference with multiple quantization options
- Optimized performance on different hardware configurations
- ARM-optimized versions available (Q4_0_4_4)
- Balance between model size and quality through various quantization options
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its comprehensive range of quantization options, allowing users to choose the perfect balance between model size, inference speed, and quality. The availability of both standard and IQ-quants makes it versatile for different use cases.
Q: What are the recommended use cases?
For general use, the Q4_K_S and Q4_K_M variants are recommended as they offer a good balance of speed and quality. For maximum quality, users should consider Q6_K or Q8_0, while those with limited resources might prefer Q2_K or Q3_K_S variants.
