TEST2-Q2.5-Lenned-14B-i1-GGUF
| Property | Value |
|---|---|
| Author | mradermacher |
| Model Type | GGUF Quantized |
| Original Model | djuna/TEST2-Q2.5-Lenned-14B |
| Available Sizes | 3.7GB - 12.2GB |
What is TEST2-Q2.5-Lenned-14B-i1-GGUF?
This is a comprehensive collection of quantized versions of the TEST2-Q2.5-Lenned-14B model, optimized for efficient deployment while maintaining various levels of performance. The model offers multiple GGUF variants with different quantization levels, allowing users to choose the optimal balance between model size, speed, and quality for their specific use case.
Implementation Details
The implementation features both standard and imatrix (IQ) quantization methods, with file sizes ranging from 3.7GB to 12.2GB. The quantization levels include Q2, Q3, Q4, Q5, and Q6 variants, each with different size and quality tradeoffs.
- IQ (imatrix) variants often provide better quality than standard quantization at similar sizes
- Q4_K_M (9.1GB) is recommended for optimal performance and speed
- Q6_K (12.2GB) offers quality comparable to static quantization
- Smaller variants (IQ1, IQ2) are available for resource-constrained environments
Core Capabilities
- Multiple quantization options for different deployment scenarios
- Optimized weight compression while maintaining model performance
- Enhanced efficiency through imatrix quantization technology
- Flexible size options from ultra-compact to high-quality variants
Frequently Asked Questions
Q: What makes this model unique?
This model provides a comprehensive range of quantization options, including innovative imatrix quantization, allowing users to precisely balance size, speed, and quality requirements.
Q: What are the recommended use cases?
For optimal performance, the Q4_K_M variant (9.1GB) is recommended. For resource-constrained environments, IQ3 variants offer good quality at smaller sizes, while Q6_K is ideal for scenarios requiring maximum quality.
