|View source on GitHub|
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.
||Who are the intended users of the model? This may include researchers, developers, and/or clients. You might also include information about the downstream users you expect to interact with your model.|
||What are the intended use cases of the model? What use cases are out-of-scope?|
||What are the known limitations of the model? This may include technical limitations, or conditions that may degrade model performance.|
||What are the known accuracy/performance tradeoffs for the model?|
||What are the ethical risks involved in application of this model? For each risk, you may also provide a mitigation strategy that you've implemented, or one that you suggest to users.|
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 )