L3-4X8B-MOE-Dark-Planet-Infinite-25B-GGUF

Introduction

L3-4X8B-MOE-Dark-Planet-Infinite-25B-GGUF is a text generation model based on LLama3 architecture, specially designed for creative writing, storytelling, and role-playing applications. It utilizes a mixture of experts approach to combine four "Dark Planet" models, each with 8 billion parameters, creating a comprehensive 25 billion parameter model.

Architecture

This model uses a mixture of experts (MoE) architecture, combining four distinct 8B models into a single entity. It operates with a maximum context length of 8192 tokens, extendable to over 32k using rope settings. The MoE setup allows for dynamic selection and combination of model outputs, enhancing the quality and variety of generated text.

Training

The training process emphasizes creative writing and storytelling abilities. The model excels in generating vivid prose, handling dialogues, and constructing rich imagery and metaphors. It supports various genres, including horror and romance, and accommodates a wide range of temperature settings to adjust creativity levels.

Guide: Running Locally

1. Setup Environment: Ensure you have the necessary environment to run the model. This includes Python, dependencies for text generation (such as Hugging Face Transformers), and a compatible GPU.
2. Download Model: Clone the model repository from Hugging Face or download it directly to your local machine.
3. Install Required Libraries: Use pip to install dependencies, ensuring compatibility with your hardware.

   pip install torch transformers
   

4. Load Model: Use a framework like PyTorch to load the model into your script.
5. Run Inference: Design your prompt and run it through the model to generate text.
6. Cloud GPUs: Consider using cloud services like AWS EC2, Google Cloud, or Azure for access to powerful GPUs if running locally is not feasible.

License

The L3-4X8B-MOE-Dark-Planet-Infinite-25B-GGUF model is distributed under the Apache 2.0 License. This allows for both personal and commercial use, provided that proper attribution is given and modifications are documented.