QwQ-32B-abliterated-i1-GGUF
| Property | Value |
|---|---|
| Original Model | QwQ-32B-abliterated |
| Author | mradermacher |
| Format | GGUF |
| Size Range | 7.4GB - 27GB |
| Repository | Hugging Face |
What is QwQ-32B-abliterated-i1-GGUF?
QwQ-32B-abliterated-i1-GGUF is a comprehensive collection of quantized versions of the original QwQ-32B-abliterated model, offering various compression levels to suit different deployment needs. The model provides multiple quantization options ranging from highly compressed 7.4GB versions to high-quality 27GB implementations.
Implementation Details
The model offers both IQ (imatrix) and standard quantization methods, with sizes ranging from IQ1_S (7.4GB) to Q6_K (27GB). Each variant represents a different trade-off between model size, inference speed, and output quality.
- Multiple quantization levels (Q2_K to Q6_K)
- IQ-based variants for optimal performance
- Size options ranging from 7.4GB to 27GB
- Optimized for different use cases and hardware constraints
Core Capabilities
- Q4_K_M (20GB) variant recommended for balanced performance
- Q6_K (27GB) offering near-original model quality
- IQ variants often outperform standard quantization at similar sizes
- Lower-size options available for resource-constrained environments
Frequently Asked Questions
Q: What makes this model unique?
This model provides a comprehensive range of quantization options, including innovative IQ-based variants that often deliver better performance than traditional quantization methods at similar file sizes. The variety of options allows users to choose the perfect balance between model size and performance for their specific use case.
Q: What are the recommended use cases?
For optimal performance, the Q4_K_M variant (20GB) is recommended as it provides a good balance of speed and quality. For those with limited resources, IQ3 variants offer reasonable performance at smaller sizes. The Q6_K variant is ideal for users requiring near-original model quality.
