L3 8 B Stheno v3.2 i1 G G U F

Introduction

L3-8B-Stheno-v3.2-i1-GGUF is a quantized model variant of the Sao10K/L3-8B-Stheno-v3.2 model, optimized for specific use cases like conversational AI and inference endpoints. It leverages datasets such as Gryphe/Opus-WritingPrompts and Sao10K/Claude-3-Opus-Instruct-15K. This model is built using the Transformers library and is available under the Creative Commons BY-NC 4.0 license.

Architecture

The model is based on the L3-8B-Stheno architecture, with weighted and static quantized variants available. These quantizations are tailored to balance size and performance, with options ranging from 2.1GB to 6.7GB, offering different trade-offs between speed and quality.

Training

Training incorporates multiple datasets focusing on English language tasks and is designed to enhance performance for inference-related applications. The quantization process facilitates efficient deployment, retaining model capabilities while reducing computational load.

Guide: Running Locally

1. Setup Environment: Ensure that you have Python and the necessary libraries installed, primarily transformers from Hugging Face.
2. Download Model: Access the model files from the Hugging Face repository, specifically the GGUF quantized versions suitable for your needs.
3. Implement: Integrate the model into your application using the Transformers library. Refer to usage examples provided by similar models if needed.
4. Run Locally: Execute the model on a local machine or use a cloud GPU service for optimal performance, such as AWS, Google Cloud, or Azure, especially for larger quantized variants.

License

This model is distributed under the Creative Commons BY-NC 4.0 license, allowing for non-commercial use with proper attribution.