Comments (2)
Thanks for creating this detailed issue @fxmarty!
One challenge with unifying the "features" used in the ONNX export and the tasks defined in the pipeline()
function is that one can have past key values that need to be differentiated, e.g. these two features are different:
causal-lm
causal-lm-with-past
Having said that, I agree that it would be nice if one could reuse the same task taxonomy from the transformers.pipeline()
function, so maybe some light refactoring can capture the majority of tasks.
cc @michaelbenayoun who knows more of the history behind the ONNX "features" names
from optimum.
Yes, I think the original feature names were chosen by looking at the classes names (BertForSequenceClassification
, etc). I think @fxmarty's first suggestion could work and is easy to implement.
from optimum.
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from optimum.