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