MT4-Gen5-GP-gemma-2-MTMMT3g4-9B-GGUF

Introduction

The MT4-Gen5-GP-gemma-2-MTMMT3g4-9B-GGUF is a quantized model available on Hugging Face, focusing on English language processing. The model is part of the Transformers library and has been quantized by the user mradermacher using the GGUF format.

Architecture

This model is based on the zelk12/MT4-Gen5-GP-gemma-2-MTMMT3g4-9B architecture. It employs static quantization techniques to optimize performance and reduce model size, with various quantization types available, each offering different balance points between size, speed, and quality.

Training

The model is quantized using static methods, while more advanced techniques like weighted or imatrix quantization are currently unavailable but may be requested. Detailed insights and comparisons for different quant types are provided to guide users in selecting the most suitable option for their needs.

Guide: Running Locally

1. Clone the Repository: Begin by cloning the model repository to your local machine.
2. Install Dependencies: Ensure you have the Transformers library installed using pip:

   pip install transformers
   

3. Download the Model Weights: Choose the appropriate quant type for your requirements and download the corresponding GGUF file.
4. Load the Model: Utilize the Transformers library to load and interact with the model:

   from transformers import AutoModel
   model = AutoModel.from_pretrained('path_to_quantized_model')
   

5. Run Inference: Use the model for your specific application, such as text generation or classification.

Cloud GPUs: For optimal performance, especially with larger quantizations, consider using cloud-based GPU services like AWS, Google Cloud, or Azure.

License

The model and its accompanying files are subject to the licensing terms provided by the original uploader on Hugging Face. Refer to the model's page for specific licensing information.