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Project description
ModelMaker
Framework and utilities for creating and validating ML models
Features
- CLI tool for creation and validation of models
- Choose from predefined templates
Install the tool
This will install the modelmaker CLI tool
git clone https://github.com/shirecoding/ModelMaker.git
cd ModelMaker
pip3 install ./
alternatively install from pypi
pip3 install model-maker
List Templates
modelmaker templates
Create a New Project
modelmaker new --project MNISTClassifier --package mnistmodel --template default
This will create the python package mnistmodel inside directory MNISTClassifier (also the main class name)
Current Templates
- default (simple classification model using mnist dataset example)
- linear_regression
- text_classification
Project Structure
- The model is packaged as an importable and installable python library
- scripts/train.py used for training the model and exporting it to saved_models
- scripts/test.py gives an example of how to use the packaged model in production
src/
MNISTClassifier/
mnistmodel/ # python model package
saved_model/ # this is where the model is saved after training
mnistmodel
scripts/
train.py # training script which imports model package, trains model, saves model to saved_model
test.py # example test script on how to use the model package in production
setup.py
README.md
.gitignore
...
Model Framework and Pipeline
- Each model inherits from an abstract class ModelInterface
- Each model must override get_model, fit_model, load_model, save_model
- Each model must define preprocess, predict, postprocess
Project details
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