document-understanding
2022.10
false
- Overview
- Document Understanding Process
- Quickstart Tutorials
- Framework Components
- ML Packages
- Pipelines
- Document Manager
- OCR Services
- Document Understanding deployed in Automation Suite
- Install and use
- First run experience
- Deploy UiPathDocumentOCR
- Deploy an out-of-the-box ML package
- Use Document Manager
- Use the Framework
- Downloading offline bundles
- Document Understanding deployed in AI Center standalone
- Deep Learning
- Licensing
- References
- UiPath.Abbyy.Activities
- UiPath.AbbyyEmbedded.Activities
- UiPath.DocumentUnderstanding.ML.Activities
- UiPath.DocumentUnderstanding.OCR.LocalServer.Activities
- UiPath.IntelligentOCR.Activities
- UiPath.OCR.Activities
- UiPath.OCR.Contracts
- UiPath.DocumentProcessing.Contracts
- UiPath.OmniPage.Activities
- UiPath.PDF.Activities
Deploy an out-of-the-box ML package
Document Understanding User Guide
Last updated Oct 17, 2024
Deploy an out-of-the-box ML package
This page describes how to deploy an out-of-the-box Document UnderstandingTM ML Package. For demonstration purposes, we are going to use the Invoices ML Package as an example.
For online installation, the Invoices model is already included in the Out of the box packages section. Go to ML Packages > Out of the box packages > UiPath Document Understanding > Invoices, and click Submit.
For offline installation, please upload the Invoices ML Package as a Zip file. To download the models, contact your Account Manager, CSM, or Support. You will receive a download link per package.
- Go to to start uploading the zip file.
- Choose Json input type and the corresponding Python language.
- Select Create.
- Navigate to the ML Skills tab from the left sidebar of AI Center and create a
new ML Skill.
Note: This can take up to 30 minutes.
- Once the ML Skill is created, double-click the ML Skill and go to Modify current deployment.
- Switch the toggle on to make the ML Skill public. You may need to wait for a few minutes and refresh the page.
- Once the ML Skill is ready, copy the URL, which is the endpoint of the
Invoices ML package for later use.
Congrats! You have successfully deployed the Invoices ML Model on AI Center.