This is to just download the ToneIt app and utilize the example
- Clone the repository
- Download (the model)[https://drive.google.com/file/d/1IpBXq09vFqbJ2RRlDDlFCmHbU3WlnpCf/view?usp=sharing] (50epochs, 16000objects)
- Run the main application via the GoogleCOLAB through the
MainApp.ipynb
file
This is to build the model from scratch yourself
- Clone the repository
- Open the
CreateModel.ipynb
file in a GoogleCOLAB environment - Upload the trainTone.txt file to the GoogleCOLAB environment
- Run the
CreateModel.ipynb
file (you can change parameters based on theHyperParameterTuning.ipynb
file) - Download the
ToneItPipeline.tar.gz
archive from the GoogleCOLAB environment - Proceed to QuickStart with your ToneItPipeline model
- Model evalution metrics are found in
CreateModel.ipynb
file for the 50epochs 16000objects model - More performance and evaluation metrics from hyperparameter tuning are in
HyperParameterTuning.ipynb
though these are trained on less epochs - The function that calls upon the model created from the other two jupyter notebooks is in
MainApp.ipynb
data/
contains the data processed via the .java code in the same directory from the original dataset used to train the models