🚀 Feature
Please consider adding PartitionSHAP
(or another fast attribution method)
Motivation
The currently available attribution methods run very long for large models like llama2 or mistral.
Pitch
The PartitionSHAP implementation from shap runs only minutes on a model like Mistral or GPT-2.
It is their best-performing explainer (runtime-wise), especially for text generation. It runs significantly quicker than any other method. The attributions are a bit less accurate the performance is very good.
As far as I know, it's the fastest model-agnostic explanation approach. Anything else using owen values should also be very fast.
Alternatives
- Any other super quick attribution method would be very welcome 😄
- I've listed fastSHAP below, which is also very fast but not proven on any LLMs.
Additional context
This is the PartitionSHAP implementation from the shap package. There's also fastSHAP, though I am not sure how applicable it would be to LLMs.
🚀 Feature
Please consider adding PartitionSHAP
(or another fast attribution method)
Motivation
The currently available attribution methods run very long for large models like llama2 or mistral.
Pitch
The PartitionSHAP implementation from shap runs only minutes on a model like Mistral or GPT-2.
It is their best-performing explainer (runtime-wise), especially for text generation. It runs significantly quicker than any other method. The attributions are a bit less accurate the performance is very good.
As far as I know, it's the fastest model-agnostic explanation approach. Anything else using owen values should also be very fast.
Alternatives
Additional context
This is the PartitionSHAP implementation from the shap package. There's also fastSHAP, though I am not sure how applicable it would be to LLMs.