llama3.1-8b-spaetzle-v90-GGUF
| Property | Value |
|---|---|
| Model Size | 8B parameters |
| Author | mradermacher |
| Source | huggingface.co/cstr/llama3.1-8b-spaetzle-v90 |
| Format | GGUF |
What is llama3.1-8b-spaetzle-v90-GGUF?
This model is a quantized version of the LLaMA 3.1 8B Spaetzle model, optimized for efficient deployment through various GGUF compression formats. It offers multiple quantization options ranging from 3.3GB to 16.2GB, allowing users to balance between model size and performance.
Implementation Details
The model provides several quantization variants, with notable options including Q4_K_S and Q4_K_M which are recommended for their optimal balance of speed and quality. The Q8_0 variant offers the highest quality at 8.6GB, while the Q2_K provides the smallest footprint at 3.3GB.
- Multiple quantization options (Q2 through Q8)
- Size ranges from 3.3GB to 16.2GB
- IQ-quants available for enhanced performance
- Optimized for different use-case requirements
Core Capabilities
- Fast inference with Q4_K variants
- High-quality output with Q6_K and Q8_0 variants
- Flexible deployment options for different hardware constraints
- Compatible with standard GGUF loaders
Frequently Asked Questions
Q: What makes this model unique?
The model offers a comprehensive range of quantization options, making it highly versatile for different deployment scenarios. The availability of both speed-optimized (Q4) and quality-optimized (Q8) variants sets it apart.
Q: What are the recommended use cases?
For most applications, the Q4_K_S or Q4_K_M variants are recommended as they provide a good balance of speed and quality. For highest quality requirements, the Q8_0 variant is suggested, while resource-constrained environments might benefit from the smaller Q2_K or Q3_K variants.
