SeQwence-14B-EvolMergev1-GGUF
| Property | Value |
|---|---|
| Parameter Count | 14.8B |
| Model Type | Conversational AI |
| Architecture | Transformer-based GGUF |
| Language | English |
What is SeQwence-14B-EvolMergev1-GGUF?
SeQwence-14B-EvolMergev1-GGUF is a quantized version of the original SeQwence-14B model, optimized for efficient deployment while maintaining performance. This implementation offers various quantization levels, from highly compressed Q2_K (5.9GB) to high-quality Q8_0 (15.8GB), allowing users to balance between model size and performance.
Implementation Details
The model features multiple quantization variants using the GGUF format, each optimized for different use cases. The implementation includes both standard and improved quantization methods (IQ-quants), with file sizes ranging from 5.9GB to 15.8GB.
- Multiple quantization options (Q2_K through Q8_0)
- Optimized versions for ARM architecture
- IQ-quants available for enhanced performance
- Weighted/imatrix variants available separately
Core Capabilities
- Efficient inference with various compression levels
- Fast execution on both standard and ARM architectures
- Flexible deployment options based on hardware constraints
- Maintained conversation quality across quantization levels
Frequently Asked Questions
Q: What makes this model unique?
The model offers an extensive range of quantization options, including specialized variants like Q4_0_4_4 optimized for ARM architecture, making it highly versatile for different deployment scenarios.
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 highest quality applications, Q8_0 is recommended, while Q2_K is suitable for resource-constrained environments.
