Aurora-SCE-12B-v2-i1-GGUF
| Property | Value |
|---|---|
| Original Model | yamatazen/Aurora-SCE-12B-v2 |
| Quantization Types | Multiple (IQ1-IQ4, Q2-Q6) |
| Size Range | 3.1GB - 10.2GB |
| Author | mradermacher |
What is Aurora-SCE-12B-v2-i1-GGUF?
Aurora-SCE-12B-v2-i1-GGUF is a comprehensive collection of quantized versions of the Aurora-SCE-12B-v2 model, optimized for different use cases and hardware constraints. The model offers various quantization methods using both standard and imatrix (IQ) approaches, providing users with flexibility in choosing between file size and performance.
Implementation Details
The model implements multiple quantization techniques, ranging from highly compressed IQ1_S (3.1GB) to high-quality Q6_K (10.2GB) versions. The implementation includes innovative imatrix quantization methods that often outperform traditional quantization at similar file sizes.
- Features weighted/imatrix quantization options for optimal performance
- Offers 21 different quantization variants
- Includes both standard (Q) and improved matrix (IQ) quantization methods
- Optimized for various hardware configurations and use cases
Core Capabilities
- Flexible deployment options with different size/quality tradeoffs
- Q4_K_M variant (7.6GB) recommended for balanced performance
- IQ3 variants generally outperform standard Q3_K quantization
- Superior compression while maintaining model quality through imatrix quantization
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its comprehensive range of quantization options, particularly the implementation of imatrix quantization techniques that often provide better quality than traditional quantization methods at similar file sizes. The various compression levels allow users to choose the optimal balance between model size and performance for their specific needs.
Q: What are the recommended use cases?
For optimal performance, the Q4_K_M variant (7.6GB) is recommended as it offers a good balance of speed and quality. For users with limited resources, IQ3 variants provide better quality than standard Q3_K quantization at similar sizes. The Q6_K variant (10.2GB) is recommended for users requiring maximum quality.
