YuLan-Mini-GGUF Model

Introduction

YuLan-Mini-GGUF is a conversational AI model supporting English and Chinese, based on the YuLan-Mini model by the RUC-GSAI-YuLan team. The model includes GGUF quantizations provided by QuantFlex, enhancing performance for specific applications without K-Quants due to tensor column constraints.

Architecture

The model leverages the base architecture of YuLan-Mini, designed for efficient conversational AI tasks. The quantized version uses the GGUF format, which optimizes the model for faster inference and reduced computational requirements.

Training

The training insights and methodology are based on the original YuLan-Mini model. Details about dataset specifics and training configurations are typically aligned with the base model's parameters, which aim to provide robust multilingual capabilities across English and Chinese.

Guide: Running Locally

To run YuLan-Mini-GGUF locally, follow these steps:

Clone the Repository: Download the model files from the Hugging Face model card page.
Install Dependencies: Ensure you have the necessary libraries installed. Consider using Python environments like venv or conda.
Run with llama.cpp: Use the llama.cpp tool, available on GitHub, to execute and interact with the model.
Hardware Considerations: For optimal performance, using cloud GPUs from platforms like AWS or Google Cloud is recommended.

License

The YuLan-Mini-GGUF model is available under the MIT License, allowing flexible use, modification, and distribution of the model in both open-source and commercial projects.