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-0.10.2510447650.tar.gz (100.1 kB view details)

Uploaded Source

Built Distribution

layer-0.10.2510447650-py3-none-any.whl (133.3 kB view details)

Uploaded Python 3

File details

Details for the file layer-0.10.2510447650.tar.gz.

File metadata

  • Download URL: layer-0.10.2510447650.tar.gz
  • Upload date:
  • Size: 100.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.13 CPython/3.8.12 Linux/5.4.0-1083-azure

File hashes

Hashes for layer-0.10.2510447650.tar.gz
Algorithm Hash digest
SHA256 07ba6fb9f97b465f849645f5eff0813487a9022c6d62099e63622472d1dea9ea
MD5 ca4b650d81d50c5ab2fd66bda194b9a6
BLAKE2b-256 3b831c160c433cde1b5ff3a54e398420bc7c949c364f16352c12f3c0c5c5079f

See more details on using hashes here.

File details

Details for the file layer-0.10.2510447650-py3-none-any.whl.

File metadata

  • Download URL: layer-0.10.2510447650-py3-none-any.whl
  • Upload date:
  • Size: 133.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.13 CPython/3.8.12 Linux/5.4.0-1083-azure

File hashes

Hashes for layer-0.10.2510447650-py3-none-any.whl
Algorithm Hash digest
SHA256 330aac454accf1914877daba8afe90d76a14d17abc72c3b11a25a5e7531f7c7a
MD5 2e1f954f0e765d345d744b18a4a92998
BLAKE2b-256 5c6d971dc68e4ad78bb27dfef541ff7ae9d92ef971546eeac542399ef0a58ee7

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