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-0.10.2840959837.tar.gz (143.9 kB view details)

Uploaded Source

Built Distribution

layer-0.10.2840959837-py3-none-any.whl (192.2 kB view details)

Uploaded Python 3

File details

Details for the file layer-0.10.2840959837.tar.gz.

File metadata

  • Download URL: layer-0.10.2840959837.tar.gz
  • Upload date:
  • Size: 143.9 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-0.10.2840959837.tar.gz
Algorithm Hash digest
SHA256 ca43ddd0d7a2299e80438cb8dac14c62b4ae14abe0dbb37f47e6bfc23b6a11c6
MD5 eeaf509b3ad126f8b27fb44d0c884b12
BLAKE2b-256 db0f3c6bfc0e6fa8ce470a8df7bc762325073546f4e4e55356781a990b917420

See more details on using hashes here.

File details

Details for the file layer-0.10.2840959837-py3-none-any.whl.

File metadata

  • Download URL: layer-0.10.2840959837-py3-none-any.whl
  • Upload date:
  • Size: 192.2 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-0.10.2840959837-py3-none-any.whl
Algorithm Hash digest
SHA256 2a6ab83557b83c512219a4d62ae19584a352ea8c7d037c3942322e1abff60a93
MD5 d5ba332836e9b0eb8fdcfd4b64f59fe8
BLAKE2b-256 b5b0143e2391b6b84e6c5dd899b7dc28b7d0f8cbc9a13bb1097952f7f72dc441

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