Loki-v2.6-8b-1024k-GGUF
| Property | Value |
|---|---|
| Parameter Count | 8.03B |
| Model Type | GGUF Quantized |
| Context Window | 1024k tokens |
| Language | English |
What is Loki-v2.6-8b-1024k-GGUF?
Loki-v2.6-8b-1024k-GGUF is a quantized version of the original Loki language model, optimized for efficient deployment and inference. This model offers multiple quantization variants ranging from 3.3GB to 16.2GB, allowing users to balance between model size, inference speed, and output quality.
Implementation Details
The model comes in various quantization formats, with notable implementations including Q4_K_S and Q4_K_M which are recommended for their optimal balance of speed and quality. The architecture supports a substantial 1024k token context window, making it suitable for processing longer text sequences.
- Multiple quantization options from Q2_K to F16
- Size variants ranging from 3.3GB to 16.2GB
- Optimized performance through GGUF format
- Extended context window capability
Core Capabilities
- Efficient text processing with various memory footprint options
- High-quality text generation with Q6_K and Q8_0 variants
- Optimized for both CPU and GPU inference
- Support for long-context applications
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for its variety of quantization options and extended context window, allowing users to choose the optimal configuration for their specific use case and hardware constraints.
Q: What are the recommended use cases?
The model is ideal for applications requiring long-context processing while operating under various hardware constraints. The Q4_K_S and Q4_K_M variants are recommended for general use, while Q6_K and Q8_0 are preferred for highest quality output.
