How does variance tuning improve Generative AI s ability to generate novel outputs

Question

With the help of code can you tell me How does variance tuning improve Generative AI's ability to generate novel outputs?

Answer 1

Variance tuning in Generative AI adjusts the model's output diversity by controlling the randomness during generation. By optimizing variance, models can produce more varied and novel outputs, preventing repetitive and deterministic results while balancing creativity and coherence.

Here is the code snippet showing how it is done:

In the above code, we are using the following key points:

• Temperature: Controls the randomness of the output (higher values generate more diverse text).
• Top-k Sampling: Limits the number of potential tokens to sample from, ensuring diversity without loss of quality.
• GPT-2 Model: Used to demonstrate how variance tuning affects text generation.

Hence, variance tuning enhances the ability of Generative AI to produce novel and diverse outputs by adjusting randomness in the generation process, increasing creativity while maintaining coherence.