This project integrates the methodologies of "STaR: Self-Taught Reasoner" and "Let’s Verify Step by Step" to enhance the capabilities of Large Language Models (LLMs) like GPT-4. The script provided is a conceptual representation, focusing on the integration of the Ollama platform or Hugging Face models with process supervision and synthetic data generation.
- Ollama Integration: Requires setting up the Ollama platform and using the correct endpoint URL.
- Model Selection: A suitable model from Hugging Face can be chosen based on task complexity.
- Synthetic Label Generation: Currently uses a basic random method. Implement a more sophisticated heuristic or a smaller model for better accuracy.
- Process Reward Model (PRM): Placeholder class, requiring specific implementation details.