LLM Evaluation
The LLM Evaluation repository provides a collection of sample notebooks and prompts designed for evaluating large language models (LLMs) and generative AI systems. This resource is particularly useful for researchers and practitioners looking to understand and assess the performance of LLMs in various contexts.
Key Features:
- Sample Notebooks: Includes Jupyter notebooks that demonstrate evaluation techniques and methodologies for LLMs.
- Prompts for Evaluation: A curated set of prompts that can be used to test and evaluate the capabilities of LLMs.
- Workshop Resources: Contains materials from evaluation workshops, including slides and additional resources for deeper learning.
- OpenAI API Integration: Some notebooks require an OpenAI API key, allowing users to leverage powerful AI models for evaluation.
Benefits:
- Hands-On Learning: Users can interact with LLMs and learn through practical examples and guided notebooks.
- Community Contributions: The repository encourages contributions from the community, fostering collaboration and knowledge sharing.
- Regular Updates: The repository is actively maintained, with updates planned for future workshops and resources.
Highlights:
- Resources for evaluating LLMs and generative AI.
- Links to conference presentations and videos for further learning.
- A focus on practical applications and real-world use cases for LLM evaluation.
