DeepSeek-R1-Distill-Qwen-32B-Uncensored-GGUF
| Property | Value |
|---|---|
| Original Model | DeepSeek-R1-Distill-Qwen-32B-Uncensored |
| Author | mradermacher |
| Format | GGUF |
| Model URL | https://huggingface.co/mradermacher/DeepSeek-R1-Distill-Qwen-32B-Uncensored-GGUF |
What is DeepSeek-R1-Distill-Qwen-32B-Uncensored-GGUF?
This is a GGUF-formatted quantized version of the DeepSeek-R1-Distill-Qwen-32B-Uncensored model, offering various compression options to balance between model size and performance. The quantization provides multiple variants ranging from 12.4GB to 34.9GB, making it suitable for different deployment scenarios and hardware constraints.
Implementation Details
The model offers several quantization types, each optimized for different use cases:
- Q2_K: Smallest size at 12.4GB
- Q4_K_S/M: Fast and recommended variants at 18.9GB/19.9GB
- Q6_K: Very good quality at 27.0GB
- Q8_0: Highest quality at 34.9GB
- IQ4_XS: Improved quantization at 18.0GB
Core Capabilities
- Multiple quantization options for different deployment needs
- Optimized performance-to-size ratios
- Support for both static and weighted/imatrix quantization
- Compatible with standard GGUF loading systems
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its variety of quantization options, allowing users to choose the optimal balance between model size and performance. It also offers both static and weighted quantization variants.
Q: What are the recommended use cases?
For most applications, the Q4_K_S or Q4_K_M variants are recommended as they offer a good balance of speed and quality. For highest quality requirements, Q8_0 is recommended, while Q2_K is suitable for environments with severe storage constraints.
