Top P, also known as Nucleus Sampling, is a strategy used in language models for text generation. Instead of choosing the most likely next word in a sequence, the model considers a set of possible next words, known as the "nucleus", based on their cumulative probability exceeding a certain threshold, P. This approach provides a balance between randomness and predictability, resulting in more diverse and realistic text generation.
In the context of tuning model parameters, Top P is very similar to temperature and it is usually recommended to only adjust one of the two.
The LLM Knowledge Base is a collection of bite-sized explanations for commonly used terms and abbreviations related to Large Language Models and Generative AI.
It's an educational resource that helps you stay up-to-date with the latest developments in AI research and its applications.