Model Selection

Learn about the process of selecting appropriate LLMs for fine-tuning.

Choosing the right LLM for fine-tuning

When fine-tuning an LLM for our specific task, it’s crucial to consider various factors before selecting a model. The initial considerations include:

Model size

LLMs are available in various sizes, and the size of a model directly affects its computational demands. Larger models typically offer better performance but require substantial computational power to operate. Depending on our requirements, we might opt for a smaller model like GPT-2, which has 124 million parameters and is more lightweight, or choose a more powerful option like Llama-2, which has 70 billion parameters and provides a higher level of performance.

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