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-0.10.2949500440.tar.gz (146.5 kB view details)

Uploaded Source

Built Distribution

layer-0.10.2949500440-py3-none-any.whl (202.4 kB view details)

Uploaded Python 3

File details

Details for the file layer-0.10.2949500440.tar.gz.

File metadata

  • Download URL: layer-0.10.2949500440.tar.gz
  • Upload date:
  • Size: 146.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.15 CPython/3.8.13 Linux/5.4.0-1086-azure

File hashes

Hashes for layer-0.10.2949500440.tar.gz
Algorithm Hash digest
SHA256 1a37a1a70458733d93fcb2f5ff574579aeab6b6dfc0bb1aeadece6bb5ea8fce2
MD5 3470b9125e8be2602dd20af58ff7e498
BLAKE2b-256 19a47533119f400dba99e106de7d2ce39a5d93b8c219e52f100ea80e29869b51

See more details on using hashes here.

File details

Details for the file layer-0.10.2949500440-py3-none-any.whl.

File metadata

  • Download URL: layer-0.10.2949500440-py3-none-any.whl
  • Upload date:
  • Size: 202.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.15 CPython/3.8.13 Linux/5.4.0-1086-azure

File hashes

Hashes for layer-0.10.2949500440-py3-none-any.whl
Algorithm Hash digest
SHA256 8965bd1b4b424285e41d0aea674a7cbe310d6c08c8782fdef76225a91c9f092b
MD5 e564ef482df648be33ee904e4916a0e7
BLAKE2b-256 9bfcb1c4710796da2b23ae2bcf92f7fdb9bf3fc04aaffe598d04fcd8e61cd0bc

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