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-0.10.2612374865.tar.gz (110.2 kB view details)

Uploaded Source

Built Distribution

layer-0.10.2612374865-py3-none-any.whl (152.4 kB view details)

Uploaded Python 3

File details

Details for the file layer-0.10.2612374865.tar.gz.

File metadata

  • Download URL: layer-0.10.2612374865.tar.gz
  • Upload date:
  • Size: 110.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.13 CPython/3.8.13 Linux/5.4.0-1085-azure

File hashes

Hashes for layer-0.10.2612374865.tar.gz
Algorithm Hash digest
SHA256 de170bc360a03b4da9b3d07276669ba70f668ad962e3007d9bfeef20d36c1961
MD5 5d70ac69f9935ef4a8a69272c82be246
BLAKE2b-256 827f70a767130ab10ac7729bbd9ec8122156d23c7a91318e4814c3100de50ea7

See more details on using hashes here.

File details

Details for the file layer-0.10.2612374865-py3-none-any.whl.

File metadata

  • Download URL: layer-0.10.2612374865-py3-none-any.whl
  • Upload date:
  • Size: 152.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.13 CPython/3.8.13 Linux/5.4.0-1085-azure

File hashes

Hashes for layer-0.10.2612374865-py3-none-any.whl
Algorithm Hash digest
SHA256 b325156ef636e939437e6b1d02101203092264b8d29e10f641773004c85eb992
MD5 fc895f3a23e057e7168121267d9480b0
BLAKE2b-256 15f7d0e683ff35db1eb2896267e2f962b63a2bc1a53e50d9b85d759ed283d9e7

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