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    <title>topic Re: Failure in mlflow.spark.load_model : Random Forrest pretrained model in Machine Learning</title>
    <link>https://community.databricks.com/t5/machine-learning/failure-in-mlflow-spark-load-model-random-forrest-pretrained/m-p/33407#M1768</link>
    <description>&lt;P&gt;Hi @Ashraf Khan​&amp;nbsp;Did you get a chance to look into Sean's response. Please let us know if you need more help on this.&lt;/P&gt;</description>
    <pubDate>Fri, 30 Sep 2022 11:27:25 GMT</pubDate>
    <dc:creator>Noopur_Nigam</dc:creator>
    <dc:date>2022-09-30T11:27:25Z</dc:date>
    <item>
      <title>Failure in mlflow.spark.load_model : Random Forrest pretrained model</title>
      <link>https://community.databricks.com/t5/machine-learning/failure-in-mlflow-spark-load-model-random-forrest-pretrained/m-p/33405#M1766</link>
      <description>&lt;PRE&gt;&lt;CODE&gt;model = mlflow.spark.load_model(model_uri=f"models:/{model_name}/{model_version}")&lt;/CODE&gt;&lt;/PRE&gt;&lt;P&gt;Log:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;An error occurred while calling o2861.load.&lt;/P&gt;&lt;P&gt;: org.apache.spark.SparkException: Job aborted due to stage failure: Task 4 in stage 4599.0 failed 4 times, most recent failure: Lost task 4.3 in stage 4599.0 (TID 3270) (10.139.64.5 executor 1): java.lang.AssertionError: assertion failed: Decision Tree load failed.  Expected largest node ID to be 53, but found 26&lt;/P&gt;</description>
      <pubDate>Fri, 26 Aug 2022 07:17:29 GMT</pubDate>
      <guid>https://community.databricks.com/t5/machine-learning/failure-in-mlflow-spark-load-model-random-forrest-pretrained/m-p/33405#M1766</guid>
      <dc:creator>ashrafkhan94</dc:creator>
      <dc:date>2022-08-26T07:17:29Z</dc:date>
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    <item>
      <title>Re: Failure in mlflow.spark.load_model : Random Forrest pretrained model</title>
      <link>https://community.databricks.com/t5/machine-learning/failure-in-mlflow-spark-load-model-random-forrest-pretrained/m-p/33406#M1767</link>
      <description>&lt;P&gt;Hm. Are you training with one version of Spark but loading in another version? though that should be pretty compatible across versions, just trying to rule that in/out.&lt;/P&gt;</description>
      <pubDate>Mon, 19 Sep 2022 22:37:55 GMT</pubDate>
      <guid>https://community.databricks.com/t5/machine-learning/failure-in-mlflow-spark-load-model-random-forrest-pretrained/m-p/33406#M1767</guid>
      <dc:creator>sean_owen</dc:creator>
      <dc:date>2022-09-19T22:37:55Z</dc:date>
    </item>
    <item>
      <title>Re: Failure in mlflow.spark.load_model : Random Forrest pretrained model</title>
      <link>https://community.databricks.com/t5/machine-learning/failure-in-mlflow-spark-load-model-random-forrest-pretrained/m-p/33407#M1768</link>
      <description>&lt;P&gt;Hi @Ashraf Khan​&amp;nbsp;Did you get a chance to look into Sean's response. Please let us know if you need more help on this.&lt;/P&gt;</description>
      <pubDate>Fri, 30 Sep 2022 11:27:25 GMT</pubDate>
      <guid>https://community.databricks.com/t5/machine-learning/failure-in-mlflow-spark-load-model-random-forrest-pretrained/m-p/33407#M1768</guid>
      <dc:creator>Noopur_Nigam</dc:creator>
      <dc:date>2022-09-30T11:27:25Z</dc:date>
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