Qwen2.5 7 B Danoia G G U F

Introduction

QWEN2.5-7B-DANOIA-GGUF is a Danish conversational model, part of the Transformers library, quantized by mradermacher. It is based on the Qwen2.5-7B-Danoia model and leverages several datasets focused on Danish language processing.

Architecture

The model is built upon the Qwen2.5-7B-Danoia architecture and utilizes datasets such as Danoia-v03, Danoia-v02, and others for training. The quantized version includes different quant types like IQ4_XS, Q4_K_S, and Q8_0, each providing varying levels of quality and computational efficiency.

Training

The model is trained using a diverse set of Danish datasets. It employs static quantization techniques, allowing different configurations based on the required balance between model size and performance.

Guide: Running Locally

1. Setup Environment: Ensure you have Python and the Transformers library installed.
2. Download Model Files: Obtain the appropriate GGUF files from the model's Hugging Face page, choosing based on your resource availability.
3. Load Model: Use the Transformers library to load the model into your environment.
4. Inference: Implement inference scripts to utilize the model for conversational tasks.

For optimal performance, consider using cloud GPU resources such as AWS EC2, Google Cloud, or Azure.

License

The model is released under the Apache-2.0 license, which allows for free use, distribution, and modification, provided that any derivatives also comply with the same license terms.