| Property | Value |
|---|---|
| Author | mradermacher |
| Original Model | Quazim0t0/Rune-14b |
| Model Format | GGUF |
| Repository | Hugging Face |
What is Rune-14b-GGUF?
Rune-14b-GGUF is a quantized version of the original Rune-14b model, optimized for efficient deployment and reduced memory footprint. This implementation offers multiple quantization options ranging from Q2 to Q8, allowing users to choose the optimal balance between model size and performance for their specific use case.
Implementation Details
The model comes in various quantization formats, each offering different size-performance trade-offs:
- Q2_K: 5.7GB - Smallest size option
- Q4_K_S/M: 8.5-9.0GB - Fast and recommended for general use
- Q6_K: 12.1GB - Very good quality
- Q8_0: 15.7GB - Fastest with best quality
Core Capabilities
- Multiple quantization options for different deployment scenarios
- Optimized formats for both memory-constrained and high-performance requirements
- IQ-quants available for improved quality at similar sizes
- Compatible with standard GGUF loaders and frameworks
Frequently Asked Questions
Q: What makes this model unique?
This model provides a comprehensive range of quantization options, making it highly versatile for different deployment scenarios. The availability of both standard and IQ-quants allows users to optimize for their specific needs.
Q: What are the recommended use cases?
For general use, the Q4_K_S/M variants (8.5-9.0GB) are recommended as they offer a good balance of speed and quality. For highest quality applications, the Q8_0 variant is recommended, while resource-constrained environments can utilize the Q2_K version.