Llama-GitVac-Turbo-8B-GGUF
| Property | Value |
|---|---|
| Author | mradermacher |
| Model Size | 8B parameters |
| Format | GGUF |
| Source Repository | Hugging Face |
What is Llama-GitVac-Turbo-8B-GGUF?
Llama-GitVac-Turbo-8B-GGUF is a quantized version of the original Llama-GitVac-Turbo-8B model, offering various compression options to optimize for different performance and storage requirements. The model provides multiple quantization variants ranging from 3.3GB to 16.2GB, making it adaptable to different hardware constraints while maintaining performance.
Implementation Details
The model features different quantization types optimized for various use cases:
- Q2_K (3.3GB): Highest compression, suitable for limited storage
- Q4_K_S/M (4.8-5.0GB): Fast and recommended for general use
- Q6_K (6.7GB): Very good quality with balanced compression
- Q8_0 (8.6GB): Fastest with best quality
- F16 (16.2GB): Full precision, uncompressed version
Core Capabilities
- Multiple quantization options for different performance needs
- Optimized for efficiency while maintaining model quality
- Compatible with standard GGUF file usage
- Supports both static and weighted/imatrix quantization variants
Frequently Asked Questions
Q: What makes this model unique?
The model offers a comprehensive range of quantization options, allowing users to choose the optimal balance between model size and performance for their specific use case. The availability of both standard and IQ-quants provides flexibility in deployment scenarios.
Q: What are the recommended use cases?
For most applications, the Q4_K_S/M variants (4.8-5.0GB) are recommended as they offer a good balance of speed and quality. For highest quality requirements, the Q8_0 variant is recommended, while Q2_K is suitable for extremely storage-constrained environments.
