This is part of an effort to adopt quanda as a language modality. Ideally, we want our explainers to support the HuggingFace AutoModelForSequenceClassification model instances (see also #8). I don't know if any of our explainer wrapper classes currently support it.
Step for this issue:
Add a model, such as this, in combination with its train dataset, as a test suite -> Can we find a "mini" version of the model? Can we only add a subset of the train set? The tests should be as quick as possible in the end, and take as little memory as possible.
In the TRAK example, they create a wrapper for an AutoModelForSequenceClassification. Can we incorporate this wrapper into our code base, so that a TRAK explainer can be initialized with an AutoModelForSequenceClassification model? Please figure out the best solution here.
Build TRAK wrapper tests for the newly added language test suit.
This is part of an effort to adopt quanda as a language modality. Ideally, we want our explainers to support the HuggingFace AutoModelForSequenceClassification model instances (see also #8). I don't know if any of our explainer wrapper classes currently support it.
Step for this issue: