Astra-v1-12B-i1-GGUF
| Property | Value |
|---|---|
| Original Model | P0x0/Astra-v1-12B |
| Quantization Type | iMatrix (weighted) |
| Model Size Range | 3.1GB - 10.2GB |
| Repository | HuggingFace |
What is Astra-v1-12B-i1-GGUF?
Astra-v1-12B-i1-GGUF is a comprehensive collection of quantized versions of the original Astra-v1-12B model, optimized using iMatrix quantization techniques. This implementation offers various quantization levels to balance between model size, performance, and quality, ranging from ultra-lightweight 3.1GB versions to high-quality 10.2GB variants.
Implementation Details
The model utilizes advanced GGUF (GGML Universal Format) with iMatrix quantization, providing multiple quantization options:
- IQ1_S/M variants (3.1-3.3GB) for minimal resource requirements
- IQ2/IQ3 series (3.7-5.8GB) offering balanced performance
- Q4_K variants (7.2-7.6GB) providing optimal size/speed/quality balance
- Q6_K variant (10.2GB) offering near-original model quality
Core Capabilities
- Multiple quantization levels for different use cases
- iMatrix quantization for improved efficiency
- Optimized performance/size tradeoffs
- Compatible with standard GGUF loaders
Frequently Asked Questions
Q: What makes this model unique?
This model's unique strength lies in its variety of quantization options using iMatrix technology, allowing users to choose the perfect balance between model size and performance for their specific use case.
Q: What are the recommended use cases?
For optimal performance, the Q4_K_M variant (7.6GB) is recommended for general use, offering a good balance of speed and quality. For resource-constrained environments, the IQ3 series provides acceptable performance at smaller sizes.
