How to serve a model in sagemaker?
based on documentation provided here , https://sagemaker.readthedocs.io/en/stable/frameworks/pytorch/using_pytorch.html#model-directory-structure, the model file saved from training is model.pth. I also read that it can be .pt extension or even bin extension. I have seen a example of pytorch_model.bin, but when i tried to serve the model with the pytorch_model.bin, it warns me that .pt or .pth file needs to exist. has anyone run into this?

Interesting question.
I'm assuming you're trying to use the PyTorch container from SageMaker in what we call &quot;script mode&quot; - where you just provide the .py entrypoint.
Have you tried to define a model_fn() function, where you specify how to load your model? The documentation talks about this here.
More details:

Before a model can be served, it must be loaded. The SageMaker PyTorch model server loads your model by invoking a model_fn function that you must provide in your script when you are not using Elastic Inference.

import torch
import os
import YOUR_MODEL_DEFINITION

def model_fn(model_dir):
    model = YOUR_MODEL_DEFINITION()
    with open(os.path.join(model_dir, 'YOUR-MODEL-FILE-HERE'), 'rb') as f:
        model.load_state_dict(torch.load(f))
    return model

Let me know if this works!
