OopsHusBot-3B-i1-GGUF
| Property | Value |
|---|---|
| Base Model | OopsHusBot-3B |
| Quantization | GGUF Format |
| Author | mradermacher |
| Original Source | alpha-ai/OopsHusBot-3B |
What is OopsHusBot-3B-i1-GGUF?
OopsHusBot-3B-i1-GGUF is a quantized version of the original OopsHusBot-3B model, optimized for efficient deployment and reduced memory footprint. This implementation offers multiple quantization variants, ranging from 1.0GB to 2.7GB, allowing users to choose the optimal balance between model size and performance.
Implementation Details
The model features both weighted and imatrix quantization methods, providing various GGUF formats optimized for different use cases. The quantization options range from lightweight IQ1_S (1.0GB) to high-quality Q6_K (2.7GB), with several intermediate options offering different trade-offs.
- Multiple quantization variants available (IQ1_S through Q6_K)
- Optimized size/quality trade-offs with IQ-quants
- Recommended variants: Q4_K_M (2.1GB) for speed and quality
- IQ4_XS (1.9GB) for optimal balance
Core Capabilities
- Efficient memory usage with various quantization options
- Support for different deployment scenarios based on resource constraints
- Improved performance with IQ-quants compared to similar-sized non-IQ variants
- Compatible with standard GGUF file usage patterns
Frequently Asked Questions
Q: What makes this model unique?
The model offers a comprehensive range of quantization options, including innovative IQ-quants that often outperform traditional quantization methods at similar sizes. This allows for flexible deployment across different hardware configurations and use cases.
Q: What are the recommended use cases?
For optimal performance, the Q4_K_M variant is recommended for general use, offering a good balance of speed and quality. For resource-constrained environments, the IQ4_XS variant provides an excellent compromise between size and performance.
