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Layer AI SDK

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Layer - Metadata Store for Production ML

Layer - Metadata store for production ML

Layer helps you build, train and track all your machine learning project metadata including ML models and datasets with semantic versioning, extensive artifact logging and dynamic reporting with local↔cloud training

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Getting Started

Install Layer:

pip install layer --upgrade

Login to your free account and initialize your project:

import layer

Decorate your training function to register your model to Layer:

from layer.decorators import model

def train():
    from sklearn import datasets
    from sklearn.svm import SVC
    iris = datasets.load_iris()
    clf = SVC(),
    return clf


Now you can fetch your model from Layer:

import layer

clf = layer.get_model("my-model:1.1").get_train()

# > SVC()

🚀 Try in Google Colab now!

Reporting bugs

You have a bug, a request or a feature? Let us know on Slack or open an issue

Contributing code

Do you want to help us build the best metadata store? Check out the Contributing Guide

Learn more

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