I am working on a machine learning task and have saved a Keras model and want to deploy it to Github (so that I can host a web demo using Streamlit and/or Flask). However, the model file is so large (> 1 GB), that I cannot upload it to Github for free.
My thought process regarding an alternative is to upload it to a cloud service such as google drive (or dropbox, box etc.) then using some sort of Python module to access it from there. So my question is, can I upload a pickle file containing a pickled Keras model to Google Drive and then access that object from a Python script? If so, how would I go about doing so?
Thank you!
I believe you can, you'll need to pip oauth2client & gspread. To access the data you would need to enable API manager on your google drive and get credentials in the form of a json file. Then you would need to share the file with the email in the credentials giving it permission. You could then port over the information as you needed to, I'm not sure how Keras works but this would be the first step.
Another important factor is that Google api is very touch when it comes to requests that are coming to fast, to overcome this put in sleep commands between each one, but if you do that this method may become way to slow for your idea.
scope = ["https://spreadsheets.google.com/feeds", 'https://www.googleapis.com/auth/spreadsheets', "https://www.googleapis.com/auth/drive.file", "https://www.googleapis.com/auth/drive"]