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Fixing bug in mlrun serving (#2872)
We've updated the code so we're updating documentation here as well.
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@ -99,7 +99,7 @@ def kfpipeline():
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outputs=['model', 'test_set'])
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# deploy our model as a serverless function, we can pass a list of models to serve
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deploy = mlrun.import_function('hub://sklearn_classifier').deploy_step(
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deploy = mlrun.import_function('hub://v2_model_server').deploy_step(
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models=[{"key": "mymodel:v1", "model_path": train.outputs['model']}])
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# test out new model server (via REST API calls)
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