Skip to main content

Layer AI SDK

Project description


Layer

License Documentation Build PyPI Contributor Covenant

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-0.10.2392033768.tar.gz (95.6 kB view details)

Uploaded Source

Built Distribution

layer-0.10.2392033768-py3-none-any.whl (129.2 kB view details)

Uploaded Python 3

File details

Details for the file layer-0.10.2392033768.tar.gz.

File metadata

  • Download URL: layer-0.10.2392033768.tar.gz
  • Upload date:
  • Size: 95.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.13 CPython/3.8.12 Linux/5.4.0-1078-azure

File hashes

Hashes for layer-0.10.2392033768.tar.gz
Algorithm Hash digest
SHA256 c248b10f5508a4edc603cc28633d600c34e90bd5e3a5806e7b0c6985c9c733e3
MD5 769754530284f2828260dd1cb0572aa3
BLAKE2b-256 442abcaebf821541ca7c7197b1a6f7e9c95ac475e9b896cf32be50251bf9bd95

See more details on using hashes here.

File details

Details for the file layer-0.10.2392033768-py3-none-any.whl.

File metadata

  • Download URL: layer-0.10.2392033768-py3-none-any.whl
  • Upload date:
  • Size: 129.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.13 CPython/3.8.12 Linux/5.4.0-1078-azure

File hashes

Hashes for layer-0.10.2392033768-py3-none-any.whl
Algorithm Hash digest
SHA256 3196f3c13385c4bc43f46c161b17c196bf574f960be72dfffe0215ae50772011
MD5 b158eb305c968a15103f661afbad6b58
BLAKE2b-256 1b06ca864d8cadb9c366c9dd9413b16b91d5fb3d0660513f74016db8803f1737

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