Connect Sonix and HuggingFace to Build Intelligent Automations
Choose a Trigger
When this happens...
New Transcript
Choose an Action
Automatically do this!
Text Classification
Language Translation
Use the Built-in Integrations
Actions and Triggers
When this happensTriggers
A trigger is an event that starts a workflow.
New Transcript
Triggers when a new transcript is complete.
Do thisActions
Action is the task that follows automatically within your Sonix integrations.
Transcribe File
Submits a new media file for transcription.
List all folder
Get all folder in Sonix.
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 Sonix and HuggingFace accounts to viaSocket. Once connected, you can set up a workflow where an event in Sonix triggers actions in HuggingFace (or vice versa).
Absolutely. You can customize how Sonix 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 Sonix 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 Sonix 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 Sonix
Sonix is an automated transcription service. We quickly and accurately convert audio and video files to text. We also provide rich editing tools so you can easily edit, annotate, and export your transcripts.
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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