Tulu 3.1 8 B Super Nova Smart G G U F

Introduction

The Tulu-3.1-8B-SuperNova-Smart-GGUF model is a quantized version of the original Tulu-3.1-8B-SuperNova-Smart, created using the llama.cpp framework. It is developed by merging multiple pre-trained language models with the help of mergekit.

Architecture

The model is constructed by merging two base models: bunnycore/Tulu-3.1-8B-SuperNova and bunnycore/Llama-3.1-8b-smart-lora. The merging process utilizes the passthrough method, combining features and capabilities of both models to enhance performance and versatility. The model operates with a bfloat16 data type.

Training

The Tulu-3.1-8B-SuperNova-Smart-GGUF is not trained from scratch but is a result of merging pre-trained models. This approach leverages the strengths of each individual model to produce a more robust and efficient language model.

Guide: Running Locally

To run the Tulu-3.1-8B-SuperNova-Smart-GGUF model locally, follow these steps:

1. Clone the Repository: Begin by cloning the model repository from Hugging Face.
2. Install Dependencies: Ensure that you have transformers and any other necessary libraries installed.
3. Load and Run the Model: Use a script to load and interact with the model, possibly requiring to set up a suitable environment like Python 3.8+.
4. Utilize Cloud GPUs: For optimal performance, consider using cloud services such as AWS, Google Cloud, or Azure to access GPUs, which can significantly speed up model inference.

License

The model is distributed under a specific license, which should be reviewed to understand usage rights and restrictions. Please refer to the model's Hugging Face page for detailed licensing information.