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aimodelshare

Open source MIT Python
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About aimodelshare

aimodelshare is a trusted, non-profit platform that enables data scientists to instantly launch machine learning models into scalable, production-ready prediction REST APIs using a single Python function. The software consists of a Python library and an integrated website at modelshare.org. When a model is deployed, its details, usage instructions, and author information are automatically published to a searchable repository. Each deployed model receives a dedicated Model Playground featuring a fully functional prediction dashboard where end-users can input text, tabular, or image data to receive live predictions online. Beyond simple deployment, the platform supports advanced community features including the creation of machine learning competitions, the upload of Jupyter notebooks for code sharing, and the exchange of model architectures and datasets. All shared artifacts automatically contribute to a comprehensive data science user portfolio. Installation is available via PyPi using pip or through conda-fo

Platforms

Web Self-hosted

Languages

Python

The mission of the AI Model Share Platform is to provide a trusted non profit repository for machine learning model prediction APIs (python library + integrated website at modelshare.org). A beta version of the platform is currently being used by Columbia University students, faculty, and staff to test and improve platform functionality.

In a matter of seconds, data scientists can launch a model into this infrastructure and end-users the world over will be able to engage their machine learning models.

  • Launch machine learning models into scalable production ready prediction REST APIs using a single Python function.

  • Details about each model, how to use the model's API, and the model's author(s) are deployed simultaneously into a searchable website at modelshare.org.

  • Deployed models receive an individual Model Playground listing information about all deployed models. Each of these pages includes a fully functional prediction dashboard that allows end-users to input text, tabular, or image data and receive live predictions.

  • Moreover, users can build on model playgrounds by 1) creating ML model competitions, 2) uploading Jupyter notebooks to share code, 3) sharing model architectures and 4) sharing data... with all shared artifacts automatically creating a data science user portfolio.

Use aimodelshare Python library to deploy your model, create a new ML competition, and more.

Find model playground web-dashboards to generate predictions now.

Installation

Install using PyPi

pip install aimodelshare

Install on Anaconda

Conda/Mamba Install ( For Mac and Linux Users Only , Windows Users should use pip method ) :

Make sure you have conda version >=4.9

You can check your conda version with:

conda --version

To update conda use:

conda update conda 

Installing aimodelshare from the conda-forge channel can be achieved by adding conda-forge to your channels with:

conda config --add channels conda-forge
conda config --set channel_priority strict

Once the conda-forge channel has been enabled, aimodelshare can be installed with conda:

conda install aimodelshare

or with mamba:

mamba install aimodelshare