Cakrawala-Llama-3.1-8B-GGUF
| Property | Value |
|---|---|
| Base Model | Llama 3.1 8B |
| Quantization Formats | Multiple GGUF variants |
| Author | mradermacher |
| Original Source | NarrativAI/Cakrawala-Llama-3.1-8B |
What is Cakrawala-Llama-3.1-8B-GGUF?
Cakrawala-Llama-3.1-8B-GGUF is a quantized version of the Cakrawala Llama 3.1 model, specifically optimized for efficient deployment and inference. It offers various GGUF quantization options ranging from 3.3GB to 16.2GB in size, allowing users to balance between model quality and resource requirements.
Implementation Details
The model provides multiple quantization variants, each optimized for different use cases:
- Q2_K (3.3GB): Smallest size option
- Q4_K_S/M (4.8-5.0GB): Recommended versions for optimal speed-quality balance
- Q6_K (6.7GB): Very good quality option
- Q8_0 (8.6GB): Highest quality quantized version
- F16 (16.2GB): Full precision version
Core Capabilities
- Efficient deployment with various size options
- Compatible with standard GGUF loaders
- Optimized for different computing resources
- Maintains model quality through careful quantization
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its variety of quantization options, making it highly adaptable to different deployment scenarios while maintaining good performance. The availability of both standard and IQ-quants provides users with flexibility in choosing the right balance between model size and quality.
Q: What are the recommended use cases?
For most applications, the Q4_K_S or Q4_K_M variants are recommended as they offer an excellent balance between speed and quality. For scenarios requiring highest quality, the Q8_0 version is recommended, while resource-constrained environments might benefit from the smaller Q2_K or Q3_K variants.
