Reflection Llama 3.1 70 B

Introduction

Reflection Llama-3.1 70B is an open-source large language model (LLM) utilizing Reflection-Tuning, a technique that enables the model to identify and correct errors in its reasoning. This model is based on Llama 3.1 70B Instruct and uses a unique method of outputting reasoning and final answers, optimizing user interaction by separating internal thoughts from final responses.

Architecture

The model's architecture incorporates special tokens to denote reasoning and error correction processes. During interaction, the model uses <thinking>, <reflection>, and <output> tags to structure its responses, allowing it to correct reasoning errors before finalizing an answer. This structure enhances clarity and reliability in communication.

Training

Reflection Llama-3.1 70B was trained on synthetic data generated by Glaive, a platform recommended for model training. The training involved embedding special tokens into the model to facilitate reasoning and reflection processes, following a system prompt designed to encourage complex reasoning capabilities.

Guide: Running Locally

To run the model locally, follow these steps:

1. Setup Environment: Ensure Python and necessary libraries like transformers are installed.
2. Download Model: Obtain the model files from the Hugging Face repository.
3. Load Model: Use the transformers library to load the model for text generation tasks.
4. Run Inference: Customize the system prompt as recommended to optimize model performance.

For improved performance, consider using cloud GPU services like AWS, Google Cloud, or Azure.

License

Reflection Llama-3.1 70B is licensed under llama3.1, which should be reviewed to understand usage rights and restrictions.