DeepSeek-R1-Distill-Llama-70B-Uncensored-v2-Unbiased-i1-GGUF
| Property | Value |
|---|---|
| Author | mradermacher |
| Model Type | GGUF Quantized Language Model |
| Base Model | DeepSeek-R1-Distill-Llama-70B |
| Size Range | 15.4GB - 58GB |
| Repository | Hugging Face |
What is DeepSeek-R1-Distill-Llama-70B-Uncensored-v2-Unbiased-i1-GGUF?
This is a specialized quantized version of the DeepSeek 70B language model, offering various compression options through GGUF format. The model provides different quantization levels to balance between model size, performance, and resource requirements, ranging from highly compressed 15.4GB versions to higher-quality 58GB implementations.
Implementation Details
The model implements different quantization techniques, including IQ (weighted/imatrix) and static quantization methods. Each variant is optimized for specific use cases, with options ranging from IQ1_S (15.4GB) to Q6_K (58GB).
- Multiple quantization options (IQ1, IQ2, IQ3, Q4, Q5, Q6)
- Weighted/imatrix quantization for improved quality
- Size options ranging from 15.4GB to 58GB
- Optimized for different performance/size trade-offs
Core Capabilities
- Efficient memory usage through various quantization levels
- Maintained model quality through sophisticated compression techniques
- Flexible deployment options based on hardware constraints
- Optimal size/speed/quality balance in mid-range quantizations
Frequently Asked Questions
Q: What makes this model unique?
The model offers a comprehensive range of quantization options, allowing users to choose the perfect balance between model size and performance. The implementation of IQ (weighted/imatrix) quantization provides better quality compared to traditional quantization methods at similar sizes.
Q: What are the recommended use cases?
For optimal performance, the Q4_K_M variant (42.6GB) is recommended as it provides a good balance of speed and quality. For resource-constrained environments, the IQ3 variants offer reasonable performance at smaller sizes. The Q6_K variant (58GB) is recommended for scenarios requiring maximum quality.
