Llama 3.2 3 B Instruct G G U F

Introduction

The Llama-3.2-3B-Instruct-GGUF is a model for text generation, quantized using GGUF, and supports eight languages, including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai. It is based on Meta's Llama architecture and is designed for conversational applications.

Architecture

Llama-3.2-3B-Instruct-GGUF is structured on the Llama model architecture developed by Meta Platforms. The model employs advanced quantization methods to optimize performance and efficiency, specifically designed for enhanced text generation capabilities.

Training

The model is trained using the Llama architecture with a focus on optimizing for text generation tasks. It includes specific quantizations using the imatrix option, which is intended to provide high-quality outputs efficiently.

Guide: Running Locally

Basic Steps

1. Install Hugging Face CLI:

   pip install -U "huggingface_hub[cli]"
   

2. Download the Model: Use the huggingface-cli to download specific quantized versions of the model.

   huggingface-cli download bartowski/Llama-3.2-3B-Instruct-GGUF --include "Llama-3.2-3B-Instruct-Q4_K_M.gguf" --local-dir ./
   

3. Select Appropriate Quantization: Choose a quantization file based on your hardware capabilities and performance requirements. Refer to the size and quality descriptions provided in the model documentation.

4. Run with LM Studio: The model can be executed using LM Studio for optimal performance on supported hardware.

Cloud GPUs

For enhanced performance, consider using cloud GPU services such as AWS, Google Cloud, or Azure, which offer scalable resources tailored for machine learning workloads.

License

The model is distributed under the Llama 3.2 Community License by Meta Platforms. It includes provisions for use, reproduction, distribution, and modification. Users must comply with the terms regarding redistribution, including providing proper attribution and adhering to the acceptable use policy. The license also contains specific restrictions for users with significant monthly active user bases, requiring separate licensing negotiations with Meta.