EEVE-Korean-Instruct-10.8B-v1.0-GGUF
| Property | Value |
|---|---|
| Parameter Count | 10.8B |
| Format | GGUF |
| Author | heegyu |
| Original Source | yanolja/EEVE-Korean-Instruct-10.8B-v1.0 |
What is EEVE-Korean-Instruct-10.8B-v1.0-GGUF?
EEVE-Korean-Instruct is a powerful Korean language model that has been optimized and quantized using llama.cpp for efficient deployment. This GGUF version enables both CPU and GPU inference, making it highly versatile for various deployment scenarios.
Implementation Details
The model has been specially formatted for instruction-following tasks and offers flexible deployment options with support for both CPU and GPU acceleration. It utilizes the GGUF format, which is optimized for efficient inference and reduced memory footprint.
- Supports both CPU and GPU inference modes
- Features 4-bit quantization for efficient memory usage
- Configurable batch size and context window of 4096 tokens
- Optimized for Korean language understanding and generation
Core Capabilities
- Korean language instruction following
- Context-aware responses
- Efficient memory utilization through quantization
- Flexible deployment options with CPU/GPU support
- Large context window handling
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its optimization for Korean language instruction-following tasks while maintaining efficient deployment capabilities through GGUF quantization. It provides a balance between performance and resource utilization.
Q: What are the recommended use cases?
The model is particularly well-suited for Korean language applications requiring instruction following, such as question-answering, text completion, and interactive dialogue systems. It's optimized for both research and production environments with its flexible deployment options.
