serializeToBundle throwing java.lang.NegativeArraySizeException

I'm trying to generate an ALS model and serialize it into an mleap bundle. When my model gets too large, serializeToBundle throws java.lang.NegativeArraySizeException. Is there a way to fix this without sacrificing data?

Traceback (most recent call last):
File "/mnt/tmp/spark-820f6826-cd62-4bbc-ad45-694147dc5f0d/mleap_model.py", line 105, in
pipelineModel.serializeToBundle("jar:file:/tmp/mleap-recommendations.zip", pipelineModel.transform(df_als))
File "/usr/local/lib/python3.6/site-packages/mleap/pyspark/spark_support.py", line 25, in serializeToBundle
serializer.serializeToBundle(self, path, dataset=dataset)
File "/usr/local/lib/python3.6/site-packages/mleap/pyspark/spark_support.py", line 42, in serializeToBundle
self._java_obj.serializeToBundle(transformer._to_java(), path, dataset._jdf)
File "/usr/lib/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
File "/usr/lib/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o469.serializeToBundle.
: java.lang.NegativeArraySizeException
at ml.combust.mleap.shaded.scalapb.GeneratedMessage$class.toByteArray(GeneratedMessageCompanion.scala:132)
at ml.bundle.Model.toByteArray(Model.scala:9)
at ml.combust.bundle.serializer.ProtoFormatModelSerializer.write(ModelSerializer.scala:60)
at ml.combust.bundle.serializer.ModelSerializer$$anonfun$write$2$$anonfun$apply$1.apply$mcV$sp(ModelSerializer.scala:89)
at ml.combust.bundle.serializer.ModelSerializer$$anonfun$write$2$$anonfun$apply$1.apply(ModelSerializer.scala:89)
at ml.combust.bundle.serializer.ModelSerializer$$anonfun$write$2$$anonfun$apply$1.apply(ModelSerializer.scala:89)
at scala.util.Try$.apply(Try.scala:192)
at ml.combust.bundle.serializer.ModelSerializer$$anonfun$write$2.apply(ModelSerializer.scala:89)
at ml.combust.bundle.serializer.ModelSerializer$$anonfun$write$2.apply(ModelSerializer.scala:89)
at scala.util.Success.flatMap(Try.scala:231)
at ml.combust.bundle.serializer.ModelSerializer.write(ModelSerializer.scala:88)
at ml.combust.bundle.serializer.NodeSerializer$$anonfun$write$1.apply(NodeSerializer.scala:85)
at ml.combust.bundle.serializer.NodeSerializer$$anonfun$write$1.apply(NodeSerializer.scala:81)
at scala.util.Try$.apply(Try.scala:192)
at ml.combust.bundle.serializer.NodeSerializer.write(NodeSerializer.scala:81)
at ml.combust.bundle.serializer.GraphSerializer$$anonfun$writeNode$1.apply(GraphSerializer.scala:34)
at ml.combust.bundle.serializer.GraphSerializer$$anonfun$writeNode$1.apply(GraphSerializer.scala:30)
at scala.util.Try$.apply(Try.scala:192)
at ml.combust.bundle.serializer.GraphSerializer.writeNode(GraphSerializer.scala:30)
at ml.combust.bundle.serializer.GraphSerializer$$anonfun$write$2.apply(GraphSerializer.scala:21)
at ml.combust.bundle.serializer.GraphSerializer$$anonfun$write$2.apply(GraphSerializer.scala:21)
at scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:57)
at scala.collection.IndexedSeqOptimized$class.foldLeft(IndexedSeqOptimized.scala:66)
at scala.collection.mutable.WrappedArray.foldLeft(WrappedArray.scala:35)
at ml.combust.bundle.serializer.GraphSerializer.write(GraphSerializer.scala:20)
at org.apache.spark.ml.bundle.ops.PipelineOp$$anon$1.store(PipelineOp.scala:21)
at org.apache.spark.ml.bundle.ops.PipelineOp$$anon$1.store(PipelineOp.scala:14)
at ml.combust.bundle.serializer.ModelSerializer$$anonfun$write$1.apply(ModelSerializer.scala:87)
at ml.combust.bundle.serializer.ModelSerializer$$anonfun$write$1.apply(ModelSerializer.scala:83)
at scala.util.Try$.apply(Try.scala:192)
at ml.combust.bundle.serializer.ModelSerializer.write(ModelSerializer.scala:83)
at ml.combust.bundle.serializer.NodeSerializer$$anonfun$write$1.apply(NodeSerializer.scala:85)
at ml.combust.bundle.serializer.NodeSerializer$$anonfun$write$1.apply(NodeSerializer.scala:81)
at scala.util.Try$.apply(Try.scala:192)
at ml.combust.bundle.serializer.NodeSerializer.write(NodeSerializer.scala:81)
at ml.combust.bundle.serializer.BundleSerializer$$anonfun$write$1.apply(BundleSerializer.scala:34)
at ml.combust.bundle.serializer.BundleSerializer$$anonfun$write$1.apply(BundleSerializer.scala:29)
at scala.util.Try$.apply(Try.scala:192)
at ml.combust.bundle.serializer.BundleSerializer.write(BundleSerializer.scala:29)
at ml.combust.bundle.BundleWriter.save(BundleWriter.scala:31)
at ml.combust.mleap.spark.SimpleSparkSerializer$$anonfun$serializeToBundleWithFormat$2.apply(SimpleSparkSerializer.scala:26)
at ml.combust.mleap.spark.SimpleSparkSerializer$$anonfun$serializeToBundleWithFormat$2.apply(SimpleSparkSerializer.scala:25)
at ml.combust.mleap.shaded.resource.AbstractManagedResource$$anonfun$5.apply(AbstractManagedResource.scala:88)
at scala.util.control.Exception$Catch$$anonfun$either$1.apply(Exception.scala:125)
at scala.util.control.Exception$Catch$$anonfun$either$1.apply(Exception.scala:125)
at scala.util.control.Exception$Catch.apply(Exception.scala:103)
at scala.util.control.Exception$Catch.either(Exception.scala:125)
at ml.combust.mleap.shaded.resource.AbstractManagedResource.acquireFor(AbstractManagedResource.scala:88)
at ml.combust.mleap.shaded.resource.ManagedResourceOperations$class.apply(ManagedResourceOperations.scala:26)
at ml.combust.mleap.shaded.resource.AbstractManagedResource.apply(AbstractManagedResource.scala:50)
at ml.combust.mleap.shaded.resource.DeferredExtractableManagedResource$$anonfun$tried$1.apply(AbstractManagedResource.scala:33)
at scala.util.Try$.apply(Try.scala:192)
at ml.combust.mleap.shaded.resource.DeferredExtractableManagedResource.tried(AbstractManagedResource.scala:33)
at ml.combust.mleap.spark.SimpleSparkSerializer.serializeToBundleWithFormat(SimpleSparkSerializer.scala:27)
at ml.combust.mleap.spark.SimpleSparkSerializer.serializeToBundle(SimpleSparkSerializer.scala:17)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)

Running Spark 2.4.4 if that helps.