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Ideally, we would be able to configure which precision to use when using the pytest framework. This may cross into importer and shark_tank generation, but there are a few ways to incorporate the feature regardless.
We should have a set of importer config options that, when specified, will trigger a generation of the model artifacts locally if a matching configuration is not found in the cloud.
This will likely need to be implemented after SHARK config is refactored into .json model cards.
The text was updated successfully, but these errors were encountered:
Ideally, we would be able to configure which precision to use when using the pytest framework. This may cross into importer and shark_tank generation, but there are a few ways to incorporate the feature regardless.
We should have a set of importer config options that, when specified, will trigger a generation of the model artifacts locally if a matching configuration is not found in the cloud.
This will likely need to be implemented after SHARK config is refactored into .json model cards.
The text was updated successfully, but these errors were encountered: