from serveit.server import ModelServer from sklearn.linear_model import LogisticRegression from sklearn.datasets import load_iris # fit logistic regression on Iris data clf = LogisticRegression() data = load_iris() clf.fit(data.data, data.target) # initialize server with a model and start serving predictions ModelServer(clf, clf.predict).serve()
Painless model inference serving via RESTful API endpoint
Customize preprocessing, validation, and postprocessing pipeline
Automatic JSON serialization, logging, and model info parsing
Currently three of the most popular Python ML libraries are supported. Interested in seeing others incoporated? Open up a pull request!
Scikit-learn
Keras
PyTorch