Connect Zoho Backstage and HuggingFace to Build Intelligent Automations
Ready to use Zoho Backstage and HuggingFace automations
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Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
New Event
Trigger when new event created.
New Attendee
Triggers when a new attendee is added.
New Checkin
Triggers when an attendee is checked in.
New Order
Trigger when new order is created
Do thisActions
Action is the task that follows automatically within your Zoho Backstage integrations.
Get Attendee Details
Get attendee details by unique id.
Create Offline Order
Creates an order in offline mode
Text Classification
Use any compatible model from the Hugging Face to classify input text using a ML model.
Language Translation
Use a compatible model from the Hugging Face Hub to translate text from one language to another.
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Frequently Asked Questions
To start, connect both your Zoho Backstage and HuggingFace accounts to viaSocket. Once connected, you can set up a workflow where an event in Zoho Backstage triggers actions in HuggingFace (or vice versa).
Absolutely. You can customize how Zoho Backstage data is recorded in HuggingFace. This includes choosing which data fields go into which fields of HuggingFace, setting up custom formats, and filtering out unwanted information.
The data sync between Zoho Backstage and HuggingFace typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Zoho Backstage and HuggingFace. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About Zoho Backstage
Zoho Backstage is an enterprise event management tool to help you create memorable event experiences.
Learn MoreAbout HuggingFace
Hugging Face is a leading platform for natural language processing (NLP) and machine learning models. It provides a wide range of pre-trained models and tools to help developers and researchers build, train, and deploy state-of-the-art machine learning applications.
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