S D R P C C H M L e1.2 12 B G G U F

Introduction

The SDRPC-CHML-E1.2-12B-GGUF model is a quantized version of the text generation model originally developed by Nitral-AI. This model is optimized using llama.cpp for various quantization formats to enhance efficiency in different computational environments.

Architecture

The model employs a 12 billion parameter architecture tailored for text generation tasks. It uses quantization techniques to reduce the model size while maintaining performance, making it suitable for use on devices with limited resources.

Training

The model has been quantized using llama.cpp's imatrix option. This process involves calibrating the model weights using a specific dataset to optimize performance across different hardware configurations.

Guide: Running Locally

1. Install Dependencies:

   • Ensure huggingface_hub is installed:

     pip install -U "huggingface_hub[cli]"
     

2. Download Files:
   Use the following command to download a specific quantized model file:

   huggingface-cli download bartowski/SDRPC-CHML-e1.2-12B-GGUF --include "SDRPC-CHML-e1.2-12B-Q4_K_M.gguf" --local-dir ./
   

3. Choose the Right File:

   • Determine your system's RAM and VRAM to select an appropriate file size.
   • For maximum speed, ensure the model fits entirely in your GPU's VRAM.
   • For optimal quality, combine system RAM and GPU VRAM capacity.

4. Run Inference:
   Execute the model in an environment like LM Studio for text generation tasks.

5. Cloud GPUs:
   Consider using cloud GPU services such as AWS, Google Cloud, or Azure for better performance if local resources are insufficient.

License

The model and related files are subject to the terms and conditions outlined on the Hugging Face platform. Users should refer to the specific license associated with the model to ensure compliance.