Light-R1-32B-GGUF
| Property | Value |
|---|---|
| Original Model | Light-R1-32B |
| Author | mradermacher |
| Model Hub | HuggingFace |
What is Light-R1-32B-GGUF?
Light-R1-32B-GGUF is a comprehensive collection of quantized versions of the original Light-R1-32B model, optimized for different use cases and hardware constraints. The model offers various quantization levels, from highly compressed Q2_K at 12.4GB to high-quality Q8_0 at 34.9GB, providing users with flexibility in choosing between size and performance.
Implementation Details
The model implements various quantization techniques, with special attention to quality-size tradeoffs. Notable quantization options include:
- Q2_K (12.4GB) - Maximum compression
- Q4_K_S/M (18.9GB/20.0GB) - Recommended for balanced performance
- Q6_K (27.0GB) - Very good quality with moderate size
- Q8_0 (34.9GB) - Highest quality, largest size
Core Capabilities
- Multiple quantization options for different hardware requirements
- IQ-quant variants offering better quality than similar-sized traditional quants
- Fast inference with recommended Q4_K variants
- Optimized for various deployment scenarios
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 quality. The availability of IQ-quant versions provides superior quality compared to traditional quantization at similar sizes.
Q: What are the recommended use cases?
For most users, the Q4_K_S or Q4_K_M variants (18.9-20.0GB) are recommended as they offer a good balance of speed and quality. For maximum quality, use Q8_0, and for minimum size requirements, consider Q2_K.
