Open Insurance L L M Llama3 8 B G G U F

Introduction

The Open-Insurance-LLM-Llama3-8B-GGUF is a fine-tuned language model designed for insurance-related queries and conversations. It uses the Llama 3 architecture and is optimized for tasks within the insurance domain, such as policy understanding and claims processing.

Architecture

The model is based on the Llama 3 architecture, featuring an 8 billion parameter configuration. It incorporates enhanced attention mechanisms and the ChatQA 1.5 instruction-tuning framework, tailored specifically for the insurance sector.

Training

The model is fine-tuned on the InsuranceQA dataset using LoRA with 8-bit precision. The training involves 20.97 million trainable parameters out of a total of 8.05 billion parameters, accounting for 0.26% of the total. The dataset contains insurance-specific question-answer pairs and domain knowledge.

Guide: Running Locally

1. Clone the Repository:
   Clone the model repository from Hugging Face's Model Hub.

2. Install Dependencies:
   Ensure transformers and pytorch are installed.

3. Download Model Files:
   Download the safetensors files and tokenizer files from the repository.

4. Load the Model:
   Use the transformers library to load the model and tokenizer.

5. Run Inference:
   Execute text generation tasks using the loaded model.

Cloud GPUs: Consider using a cloud provider like AWS, GCP, or Azure for access to powerful GPUs suitable for running large models.

License

The model is released under the llama3 license. Please review the specific terms and conditions applicable to its use.