ChatWaifu_32B_reasoning-i1-GGUF
| Property | Value |
|---|---|
| Original Model | ChatWaifu_32B_reasoning |
| Quantization Types | Multiple GGUF variants |
| Size Range | 7.4GB - 27GB |
| Author | mradermacher |
| Model Hub | Hugging Face |
What is ChatWaifu_32B_reasoning-i1-GGUF?
ChatWaifu_32B_reasoning-i1-GGUF is a comprehensive collection of quantized versions of the original ChatWaifu 32B reasoning model. This implementation offers various GGUF formats with different compression levels, allowing users to choose the optimal balance between model size, inference speed, and output quality.
Implementation Details
The model provides multiple quantization types using both standard and IQ (imatrix) compression techniques. The quantization variants range from highly compressed i1-IQ1_S (7.4GB) to high-quality Q6_K (27GB). Each variant is optimized for different use cases and hardware configurations.
- Implements weighted/imatrix quantization methods
- Offers 21 different compression variants
- Features both IQ and standard quantization options
- Provides options for different hardware capabilities
Core Capabilities
- Flexible deployment options with various size/quality tradeoffs
- Optimized performance with IQ-quants often outperforming similar-sized standard quants
- Recommended Q4_K_M variant (19.9GB) offering optimal balance of speed and quality
- Support for both high-compression (7.4GB) and high-quality (27GB) use cases
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its comprehensive range of quantization options, particularly the implementation of imatrix quantization techniques that often provide better quality than traditional quantization at similar sizes.
Q: What are the recommended use cases?
For most users, the Q4_K_M variant (19.9GB) is recommended as it provides an optimal balance of speed and quality. For resource-constrained environments, the IQ2 and IQ3 variants offer reasonable performance at smaller sizes. The Q6_K variant is suitable for users prioritizing quality over size.
