Hi everyone,
I am experimenting with recently released Sagemaker Serverless inference thanks to Julien Simon’s tutorial
Following it I managed to train a custom DistillBERT model locally, upload to S3 and create a Serverless checkpoint that works.
Right now I am pushing it further by trying it with LayoutLMv2 model.
However, it is not clear to me how to pass inputs to it. For example in DistillBert I just create input like this test_data_16 = {'inputs': 'Amazing!'} and pass it as JSON in invoke_endpoint function.
In LayoutLMv2 input consists of three parts: image, text and bounding boxes. What keys do I use to pass them ? Here is the link to the call of the processor 1
Second question is: It is not clear to me how to make modifications to the default settings of processor when creating the endpoint. For example, I would like to set the flag only_label_first_subword True by default in the processor. How to do that?
Thanks!