Sue_Ann_11B-GGUF
| Property | Value |
|---|---|
| Parameter Count | 10.7B parameters |
| Model Type | Transformer |
| Language | English |
| Framework | GGUF |
What is Sue_Ann_11B-GGUF?
Sue_Ann_11B-GGUF is a comprehensive quantized version of the original Sue_Ann_11B model, offering various optimization levels for different use cases. This model represents a significant advancement in making large language models more accessible and deployable across different hardware configurations.
Implementation Details
The model is available in multiple quantization formats, ranging from lightweight Q2_K (4.1GB) to full precision F16 (21.6GB). Each variant offers different trade-offs between model size, inference speed, and output quality.
- Multiple quantization options including Q2_K, Q3_K_S, Q4_K_M, and more
- Optimized versions for different hardware configurations
- File sizes ranging from 4.1GB to 21.6GB
- Special IQ4_XS variant for balanced performance
Core Capabilities
- Fast inference with recommended Q4_K_S and Q4_K_M variants
- High-quality output with Q6_K and Q8_0 versions
- Efficient memory usage with various compression levels
- ARM-optimized versions available
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its comprehensive range of quantization options, allowing users to choose the perfect balance between model size, speed, and quality for their specific use case.
Q: What are the recommended use cases?
For general usage, the Q4_K_S and Q4_K_M variants are recommended as they offer a good balance of speed and quality. For highest quality outputs, the Q6_K or Q8_0 variants are recommended, while Q2_K is suitable for resource-constrained environments.
