LLM Parameters

LLM Parameters refer to the elements within Large Language Models (LLMs) that dictate the model's behavior and language processing abilities.

LLM Parameters in practice

1. Learning: During training, parameters adjust to predict words based on prior context.
2. Mapping Relationships: Collectively, parameters form relationships between words and concepts in the training data.
3. Temperature Regulation: A special parameter that influences the randomness of model outputs.
4. Contribution to Architecture: They form the foundation of an LLM's ability to understand and generate language.
5. Benchmark Setting: Adjustments to parameters are evaluated against set performance benchmarks.