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-0.10.2693035013.tar.gz (130.7 kB view details)

Uploaded Source

Built Distribution

layer-0.10.2693035013-py3-none-any.whl (176.8 kB view details)

Uploaded Python 3

File details

Details for the file layer-0.10.2693035013.tar.gz.

File metadata

  • Download URL: layer-0.10.2693035013.tar.gz
  • Upload date:
  • Size: 130.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.14 CPython/3.8.13 Linux/5.4.0-1085-azure

File hashes

Hashes for layer-0.10.2693035013.tar.gz
Algorithm Hash digest
SHA256 27744022259cd17f4071706025b0e0bc1ac5d9065c70d3f20227d21eaa4d886f
MD5 cedbb4dfc091df83a33f46c3b1f276ce
BLAKE2b-256 7821a8cc0fca34f0413fbef67eae8aaf9f0c3e5e3c65004fe256e25f7be7ef9e

See more details on using hashes here.

File details

Details for the file layer-0.10.2693035013-py3-none-any.whl.

File metadata

  • Download URL: layer-0.10.2693035013-py3-none-any.whl
  • Upload date:
  • Size: 176.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.14 CPython/3.8.13 Linux/5.4.0-1085-azure

File hashes

Hashes for layer-0.10.2693035013-py3-none-any.whl
Algorithm Hash digest
SHA256 26461ccb70b89e7a98b9d97be062345e50426c8e91d85144c9a259762bcee213
MD5 20f2982a62295e00143b4d6f04adad2f
BLAKE2b-256 7fc7d1aa6781e67f1ec56f03be75d9f53f65f102d04ba14358176935c0cfb390

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