Load endpoint? about sagemaker-python-sdk

[winstonaws]

If you have an existing endpoint, you just need to create a Predictor object and provide it your endpoint name. This will give you an object that is the same as the object created by the Estimators in the end-to-end examples. Then, simply call its predict() method.

You can either use the generic RealTimePredictor class, which does not do any serialization/deserialization logic on your input, but can be configured to do so through constructor arguments:
http://sagemaker.readthedocs.io/en/stable/predictors.html

Or you can use the TensorFlow / MXNet specific predictor classes, which have default serialization/deserialization logic:
http://sagemaker.readthedocs.io/en/stable/sagemaker.tensorflow.html#tensorflow-predictor
http://sagemaker.readthedocs.io/en/stable/sagemaker.mxnet.html#mxnet-predictor

Example code using the TensorFlow predictor:

from sagemaker.tensorflow import TensorFlowPredictor

predictor = TensorFlowPredictor('myexistingendpoint')
result = predictor.predict(['my request body'])

[winstonaws]

Added answer to the FAQ on our README as well. Please reopen if you have further questions.