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- 1064 Views
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After much digging, observed i was using standard runtime. Once i switched to ML runtime of databricks, issue was resolved. To use Feature Store capability, ensure that you select a Databricks Runtime ML version from the Databricks Runtime Version dr...
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This is mentioned in:https://learn.microsoft.com/en-us/azure/databricks/mlflow/create-manage-serverless-model-endpointswith api call example, while in:https://learn.microsoft.com/en-us/answers/questions/892678/how-to-enable-databricks-model-serving-w...
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Hi @Thou Mather​ , Did you get a chance to go through this doc?
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I'm trying out managed MLflow on Databricks Community edition, with tracking data saved on Databricks and artifacts saved on my own AWS S3 bucket. I created one experiment and logged 768 runs in the experiment. When I try to get the list of the runs ...
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Hi @jae baak​ Hope all is well! Just wanted to check in if you were able to resolve your issue and would you be happy to share the solution or mark an answer as best? Else please let us know if you need more help. We'd love to hear from you.Thanks!
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Hi,is there a way to get the time stamp of the last update of a feature store table with the feature store client API? The creation time stamp can be querried as: feature_store.FeatureStoreClient().get_feature_table(name="my.table").creation_timestam...
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(The question is about querying table metadata, not creating one)I can confirm that there isn't a way to query this, not that I can see in the current API in 10.2
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Yes, you can use the API https://www.mlflow.org/docs/latest/python_api/index.html
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There are many ways you can retrieve experiments results using the mlflow API (see example if you want to retrieve and display for only a specific model (assuming you have the `model_name`:best_models = mlflow.search_runs(filter_string=f'tags.model="...
