Meta has recently released the largest version of its mostly free Llama 3 artificial intelligence model, boasting impressive multilingual capabilities and superior general performance.
With 405 billion parameters, this new version is significantly larger than its predecessor released last year.
But what exactly are these parameters? Does more parameters means better model?
This document provides a comprehensive overview of parameters in generative AI models.
It covers:
1. What parameters are.
2. The different types of parameters.
3. How parameters are learned.
4. The impact of parameters on the output of AI models.
5. The trade-offs between having more parameters (better performance but higher computational cost) and fewer parameters.
Parameters in AI models are crucial elements that determine the model’s ability to generate responses to user queries. They play a pivotal role in the functionality and performance of AI systems.
Follow along for easy to understand content on Generative AI and Data Science.
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