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-0.10.2430149265.tar.gz (98.7 kB view details)

Uploaded Source

Built Distribution

layer-0.10.2430149265-py3-none-any.whl (133.6 kB view details)

Uploaded Python 3

File details

Details for the file layer-0.10.2430149265.tar.gz.

File metadata

  • Download URL: layer-0.10.2430149265.tar.gz
  • Upload date:
  • Size: 98.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.13 CPython/3.8.12 Linux/5.4.0-1080-azure

File hashes

Hashes for layer-0.10.2430149265.tar.gz
Algorithm Hash digest
SHA256 768a3bebed66b19a7fc7201b5fdfc7c76fc41e0066365c0c8f97691c18e36c28
MD5 4d365ee6b424cd79cf4cc651607ad82b
BLAKE2b-256 13d24668f8cb8c4d8ed4b954c9f4821a6c173766680d22bffd8839c7b51eaf0a

See more details on using hashes here.

File details

Details for the file layer-0.10.2430149265-py3-none-any.whl.

File metadata

  • Download URL: layer-0.10.2430149265-py3-none-any.whl
  • Upload date:
  • Size: 133.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.13 CPython/3.8.12 Linux/5.4.0-1080-azure

File hashes

Hashes for layer-0.10.2430149265-py3-none-any.whl
Algorithm Hash digest
SHA256 3b33df53d01f75c16cf75540b1fae4d7cdbb74de6fc6f946d2d31c49fc1639a9
MD5 5fbe18f5a8e9df095328868cc73cc95c
BLAKE2b-256 533cadbe2d7f66ab447ebac8f9c33895510d2b5748935071cb7d29d747f7357d

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