Llama 3.2 Taiwan 3 B Instruct G G U F

Introduction
The Llama-3.2-Taiwan-3B-Instruct-GGUF model is a variant of the Llama-3.2 series, focused on text generation. It supports multiple languages, including Chinese (Traditional), English, Japanese, Korean, French, Italian, and German. The model is designed for conversational applications and is compatible with inference endpoints.

Architecture
The model is based on the Llama architecture and has been processed using the llama.cpp library, transforming it into a .gguf format and various quantized versions. It belongs to the Llama Factory collection and is tagged with ROC and Taiwan-related identifiers.

Training
The model leverages the Llama-3.2 architecture, fine-tuned for instructive and conversational tasks across seven languages. The quantization process employed might cause occasional outputs in simplified Chinese, an issue noted but not yet fully addressed.

Guide: Running Locally

1. Setup Environment: Ensure you have Python and necessary dependencies installed. Clone the llama.cpp repository.
2. Download Model: Obtain the model files from the Hugging Face model card page.
3. Install Requirements: Run the provided scripts to set up the environment and dependencies.
4. Run Inference: Use the llama.cpp library to load and run the model locally.
5. Cloud GPUs: For enhanced performance, consider using cloud GPU services like AWS, Google Cloud, or Azure.

License
The model is distributed under the llama3.2 license. Users are advised to review the license terms before use.