Skip to main content

Layer AI SDK

Project description


Layer

License Documentation Build PyPI Contributor Covenant

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

Start for Free now!

Getting Started

Install Layer:

pip install layer --upgrade

Login to your free account and initialize your project:

import layer
layer.login()
layer.init("my-first-project")

Decorate your training function to register your model to Layer:

from layer.decorators import model

@model("my-model")
def train():
    from sklearn import datasets
    from sklearn.svm import SVC
    iris = datasets.load_iris()
    clf = SVC()
    clf.fit(iris.data, iris.target)
    return clf

train()

Now you can fetch your model from Layer:

import layer

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

# > 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

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

layer-0.10.2705460579.tar.gz (132.4 kB view details)

Uploaded Source

Built Distribution

layer-0.10.2705460579-py3-none-any.whl (178.9 kB view details)

Uploaded Python 3

File details

Details for the file layer-0.10.2705460579.tar.gz.

File metadata

  • Download URL: layer-0.10.2705460579.tar.gz
  • Upload date:
  • Size: 132.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.14 CPython/3.8.13 Linux/5.4.0-1086-azure

File hashes

Hashes for layer-0.10.2705460579.tar.gz
Algorithm Hash digest
SHA256 1c843713b5dbd747989bd869b3d5ef67758caefd5804401142c5c2ffdaedc3f2
MD5 d0f68d6a83a8a8475edace7c0860c037
BLAKE2b-256 a613f7e599e08575a50bc84abd96d813849d6c0c67b9afa6ce5ea8fb7a832749

See more details on using hashes here.

File details

Details for the file layer-0.10.2705460579-py3-none-any.whl.

File metadata

  • Download URL: layer-0.10.2705460579-py3-none-any.whl
  • Upload date:
  • Size: 178.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.14 CPython/3.8.13 Linux/5.4.0-1086-azure

File hashes

Hashes for layer-0.10.2705460579-py3-none-any.whl
Algorithm Hash digest
SHA256 5d3c9d28207fbb9de481eb997edab36761c21d16f8e68cb76dc0e19f3f794469
MD5 fa49fe1f89b8e1fda666a4e41ac82419
BLAKE2b-256 870ea4d8aebfb5d02708dd8cb48541501e6a4a91bb793b175950d4dedf410a96

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page