How to optimize an LLM with Pruned Attention Heads for mobile inference

Question

Can i know How to optimize an LLM with Pruned Attention Heads for mobile inference.

Answer 1

You can optimize an LLM for mobile inference by pruning redundant attention heads to reduce computational complexity while retaining core model performance.

Here is the code snippet below:

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

• Selectively removes specified attention heads at runtime.

• Adjusts QKV tensors dynamically based on active heads.

• Maintains full attention logic for the remaining heads.

Hence, pruning attention heads allows significant optimization of LLMs for mobile and edge deployment without major performance loss.