Rin-9B-GGUF
| Property | Value |
|---|---|
| Author | mradermacher |
| Original Model | meguscx/Rin-9B |
| Format | GGUF |
| Model URL | Hugging Face Repository |
What is Rin-9B-GGUF?
Rin-9B-GGUF is a quantized version of the original Rin-9B model, optimized for efficient deployment and reduced storage requirements. The model offers various quantization formats ranging from highly compressed 3.9GB versions to full 16-bit precision at 18.6GB, allowing users to balance between model size and performance.
Implementation Details
The model provides multiple quantization variants, each optimized for different use cases:
- Q2_K (3.9GB): Highest compression, smallest file size
- Q4_K_S/M (5.6-5.9GB): Fast and recommended for general use
- Q6_K (7.7GB): Very good quality with balanced compression
- Q8_0 (9.9GB): Fastest execution with best quality
- F16 (18.6GB): Full 16-bit precision, uncompressed
Core Capabilities
- Multiple quantization options for different deployment scenarios
- Optimized for various compute environments
- Compatible with standard GGUF loaders
- Balanced options between model size and quality
Frequently Asked Questions
Q: What makes this model unique?
This model offers a comprehensive range of quantization options, making it highly versatile for different deployment scenarios. The availability of multiple compression levels allows users to choose the optimal balance between model size and performance.
Q: What are the recommended use cases?
For most applications, the Q4_K_S or Q4_K_M variants (5.6-5.9GB) are recommended as they offer a good balance of speed and quality. For highest quality requirements, the Q8_0 variant is recommended, while resource-constrained environments might benefit from the Q2_K variant.
