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I have tried the following way. It worked, but it is giving a different prediction in Flask vs Jupyter (which is correct)

pickledFile = _pickle.dumps(trained_model)
cursor.execute("INSERT INTO trained_models(name, model, mod_date) VALUES (%s, _binary%s, %s);",("model1",pickledFile, datetime.now()))


cursor.execute("SELECT model, name FROM trained_models where mod_date = select MAX(date) FROM trained_models);")
  blob_file = cursor.fetchone()[0]
  write_file(blob_file, 'load_model')
  loaded_model = joblib.load('load_model')

loaded_model.predict(x)

This didn't work though:

with open(blob_file, 'rb') as f:
      model = pickle.load(f)

What is the best way?

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