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-0.10.2590092392.tar.gz (108.9 kB view details)

Uploaded Source

Built Distribution

layer-0.10.2590092392-py3-none-any.whl (150.5 kB view details)

Uploaded Python 3

File details

Details for the file layer-0.10.2590092392.tar.gz.

File metadata

  • Download URL: layer-0.10.2590092392.tar.gz
  • Upload date:
  • Size: 108.9 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-0.10.2590092392.tar.gz
Algorithm Hash digest
SHA256 ccd5b68c475d0ffe95880be2adce1d5f2a1a9c2aeab607387af2850bd956e8c1
MD5 7950c6cbf4cc57fb6f986ed29c4e2209
BLAKE2b-256 4ffd12499abb59d45f04f0e7b2adf30fe54073076914c58f04095f0be848685b

See more details on using hashes here.

File details

Details for the file layer-0.10.2590092392-py3-none-any.whl.

File metadata

  • Download URL: layer-0.10.2590092392-py3-none-any.whl
  • Upload date:
  • Size: 150.5 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-0.10.2590092392-py3-none-any.whl
Algorithm Hash digest
SHA256 1c1b4759488b42e7a7c772bfeaf7d87aebcf7e01f84728b8b86d6b5e4e132414
MD5 686f7221344bad4c4a5b68bc05204bd5
BLAKE2b-256 e437aa498e542e1782777295e7fd14dd9af9bd409c2192bb2d21512047c051a0

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