Connect HuggingFace and Twitch to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for HuggingFace
Choose an Action
Automatically do this!
Create a Broadcast
Ready to use HuggingFace and Twitch automations
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Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
New Live Stream by Streamer
Triggers when a new stream goes live that matches any game and language specified.
Do thisActions
Action is the task that follows automatically within your HuggingFace integrations.
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.
Create a Broadcast
Creating a new broadcasting segment.
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Frequently Asked Questions
To start, connect both your HuggingFace and Twitch accounts to viaSocket. Once connected, you can set up a workflow where an event in HuggingFace triggers actions in Twitch (or vice versa).
Absolutely. You can customize how HuggingFace data is recorded in Twitch. This includes choosing which data fields go into which fields of Twitch, setting up custom formats, and filtering out unwanted information.
The data sync between HuggingFace and Twitch 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 Twitch. 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 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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