I am using a custom inference script for a Huggingface embedding model in an AWS SageMaker TorchServe container. My script accepts JSON input in the following format:

{
  "inputs": ["chunk1", "chunk2", "chunk3", "chunk4", ...]
}

When I send a large number of chunks in this JSON, it appears to hit a size limit in the SageMaker TorchServe image, resulting in the following error:

io.netty.handler.codec.CorruptedFrameException: Message size exceed limit: 102970662

Is it possible to increase the size limit in TorchServe settings within AWS SageMaker? If so, how can this be achieved?

I did not find any documentation in aws. So I tried adding the properties file in the folder of model.tar.gz. But it did not work.