Eridanus-Opus-14B-r999-GGUF
| Property | Value |
|---|---|
| Author | mradermacher |
| Model Size | 14B parameters |
| Format | GGUF |
| Source | Hugging Face Repository |
What is Eridanus-Opus-14B-r999-GGUF?
Eridanus-Opus-14B-r999-GGUF is a quantized version of the Eridanus-Opus language model, optimized for efficient deployment and reduced storage requirements while maintaining performance. This implementation offers multiple quantization options, allowing users to balance between model size and quality based on their specific needs.
Implementation Details
The model provides various quantization levels ranging from Q2 to Q8, with file sizes spanning from 5.9GB to 15.8GB. Notable implementations include Q4_K_S and Q4_K_M variants which are recommended for their optimal balance of speed and quality, while Q8_0 offers the highest quality at 15.8GB.
- Q2_K: Smallest size at 5.9GB
- Q4_K_S/M: Recommended for balanced performance (8.7-9.1GB)
- Q6_K: Very good quality at 12.2GB
- Q8_0: Best quality option at 15.8GB
Core Capabilities
- Multiple quantization options for different deployment scenarios
- Optimized for efficient inference
- Balanced performance-to-size ratio options
- Support for both standard and IQ-based quantization
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its variety of quantization options, allowing users to choose the optimal balance between model size and performance. It offers both standard and IQ-based quantization methods, with special attention to efficiency in deployment scenarios.
Q: What are the recommended use cases?
The model is particularly well-suited for deployment scenarios where storage space or computational resources are limited. The Q4_K variants are recommended for general use, while Q8_0 is ideal for applications requiring maximum quality.
