How can SHAP values or LIME be applied to improve interpretability in generative AI

Question

Can i know How can SHAP values or LIME be applied to improve interpretability in generative AI?

Answer 1

You can apply SHAP or LIME to generative AI models by analyzing the influence of input features on the model’s outputs to enhance interpretability.

Here is the code snippet below:

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

• Loaded a pre-trained generative model using Hugging Face’s pipeline.

• Wrapped the model with a prediction function suitable for SHAP analysis.

• Used SHAP's text masker to apply the explainer on token-level variations.

• Visualized the SHAP values to interpret influential input tokens.

Hence, this approach enables interpretability by highlighting which parts of the input text contribute most to the generated output.