Most efficient way to load machine learning model (.h5) into web app?

I have trained a tensorflow model and saved it in the form of a .h5 file, about the size of 700mb. What’s the most efficient way to load this into the web app. I have tried storing it on digitalOcean space, but loading is not very efficient, takes about over 45 seconds. Any tips for speeding this up? Below is the code I used to load the model.

def load():
    session1 = session.Session()
    client = session1.client('s3',

    model_object = client.get_object(Bucket=BUCKET_NAME, Key=WEIGHTS_FILE)
    model_content = model_object['Body'].read()
    with tempfile.NamedTemporaryFile(suffix='.h5', delete=False) as fp:
        model_path =
    return model_path

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Jeff Braunstein
DigitalOcean Employee
DigitalOcean Employee badge
May 2, 2023

Hi There, can you share where you are running this app relative to the bucket? Are they in the same datacenter?

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