
When this happens...
Automatically do this!
Create a campaign
Add contact to a campaign
Create a LinkedIn campaign
Add contact to a LinkedIn campaign
Create an advanced campaign
List campaigns
Add Contact to blacklist
Search Linkedin Campaign
Search advanced campaigns
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When this happensTriggers
A trigger is an event that starts a workflow.
Action is the task that follows automatically within your HuggingFace integrations.
Use any compatible model from the Hugging Face to classify input text using a ML model.
Use a compatible model from the Hugging Face Hub to translate text from one language to another.
Create a new campaign with targeted email lists and content setup.
Add a contact to a specific campaign for targeted outreach and engagement.
The action "Create a LinkedIn campaign" initiates a new LinkedIn campaign via API.
The action "Add contact to a LinkedIn campaign" adds contacts to your campaign.

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Workflow automation is the process of using technology to execute repetitive tasks with minimal human intervention, creating a seamless flow of activities.
To start, connect both your HuggingFace and Emelia accounts to viaSocket. Once connected, you can set up a workflow where an event in HuggingFace triggers actions in Emelia (or vice versa).
Absolutely. You can customize how HuggingFace data is recorded in Emelia. This includes choosing which data fields go into which fields of Emelia, setting up custom formats, and filtering out unwanted information.
The data sync between HuggingFace and Emelia 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 HuggingFace and Emelia. 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.
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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