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Considerations related to model construction, training, and application.
model_card_toolkit.Considerations( users: List[
model_card_toolkit.User] = dataclasses.field(default_factory=list), use_cases: List[
model_card_toolkit.UseCase] = dataclasses.field(default_factory=list), limitations: List[
model_card_toolkit.Limitation] = dataclasses.field(default_factory=list), tradeoffs: List[
model_card_toolkit.Tradeoff] = dataclasses.field(default_factory=list), ethical_considerations: List[
model_card_toolkit.Risk] = dataclasses.field(default_factory=list), _proto_type: dataclasses.InitVar[type(model_card_pb2.Considerations)] = model_card_pb2.Considerations )
The considerations section includes qualitative information about your model, including some analysis of its risks and limitations. As such, this section usually requires careful consideration, and conversations with many relevant stakeholders, including other model developers, dataset producers, and downstream users likely to interact with your model, or be affected by its outputs.
Clear the subfields of this BaseModelCardField.
copy_from_proto( proto: message.Message ) -> 'BaseModelCardField'
Copies the contents of the model card proto into current object.
merge_from_proto( proto: message.Message ) -> 'BaseModelCardField'
Merges the contents of the model card proto into current object.
to_dict() -> Dict[str, Any]
Convert your model card to a python dictionary.
to_json() -> str
Convert this class object to json.
to_proto() -> message.Message
Convert this class object to the proto.
__eq__( other )
__len__() -> int
Returns the number of items in a field. Ignores None values recursively, so the length of a field that only contains another field that has all None values would be 0.