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-0.10.2517581172.tar.gz (100.1 kB view details)

Uploaded Source

Built Distribution

layer-0.10.2517581172-py3-none-any.whl (133.3 kB view details)

Uploaded Python 3

File details

Details for the file layer-0.10.2517581172.tar.gz.

File metadata

  • Download URL: layer-0.10.2517581172.tar.gz
  • Upload date:
  • Size: 100.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.13 CPython/3.8.12 Linux/5.4.0-1083-azure

File hashes

Hashes for layer-0.10.2517581172.tar.gz
Algorithm Hash digest
SHA256 b498619ecabccc31f4604565e4bbb590e0c5f117398bac1c38cfcc4687e2153c
MD5 35889302a273a653cfe8c4bff4b0c96a
BLAKE2b-256 0bd0820b9ace8c8037b88672cea0bf160ab0013851a8c5804cdbba7ef5e08852

See more details on using hashes here.

File details

Details for the file layer-0.10.2517581172-py3-none-any.whl.

File metadata

  • Download URL: layer-0.10.2517581172-py3-none-any.whl
  • Upload date:
  • Size: 133.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.13 CPython/3.8.12 Linux/5.4.0-1083-azure

File hashes

Hashes for layer-0.10.2517581172-py3-none-any.whl
Algorithm Hash digest
SHA256 8f57964bd838afb8ac4b13dce013dcb4eda7fc6582656961900130096e5ee468
MD5 74e5f730caec80f6abd7e45f83a117d0
BLAKE2b-256 ac0d31d39b66dd7a601dfcf6c79038797c2b11311ca8ee3fe31334ff809ff7a3

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