GitHub - astorfi/LLM-Alignment-Project-Template: A comprehensive template for aligning large language models (LLMs) using Reinforcement Learning from Human Feedback (RLHF), transfer learning, and more. Build your own customizable LLM alignment solution with ease.
Nov 23, 2024 - github.com
The LLM Alignment Template is a comprehensive tool designed for aligning large language models (LLMs) and serves as a template for building your own LLM alignment application. It provides a full stack of functionality, including training, fine-tuning, deploying, and monitoring LLMs using Reinforcement Learning from Human Feedback (RLHF). The project also integrates evaluation metrics to ensure ethical and effective use of language models and offers a user-friendly interface for managing alignment, visualizing training metrics, and deploying at scale.
The template features an interactive web interface, training with RLHF, data augmentation & preprocessing, transfer learning, scalable deployment, model explainability, and a user feedback loop. It also includes a detailed project structure, setup instructions, and deployment guidelines. The project is open for contributions and is licensed under the MIT License. The author of the project is Amirsina Torfi, who can be contacted via email for further queries.
Key takeaways:
The LLM Alignment Template is a comprehensive tool for aligning large language models (LLMs) and serves as a powerful template for building your own LLM alignment application.
The template provides a full stack of functionality, including training, fine-tuning, deploying, and monitoring LLMs using Reinforcement Learning from Human Feedback (RLHF).
It offers features like an interactive web interface, training with RLHF, data augmentation & preprocessing, transfer learning, scalable deployment, model explainability, and a user feedback loop.
The project is open for contributions and is licensed under the MIT License.
