Connect NileDesk and HuggingFace to Build Intelligent Automations
Enable Integrations or automations with these events of NileDesk and HuggingFace
Enable Integrations or automations with these events of NileDesk and HuggingFace
Actions
Create Draft Board Item
Create a new board item and save it as a draft.
Create Draft Process Flow Item
Create a new process flow item and save it as a draft.
Create Process Item
Create and submit a new process item
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 NileDesk and HuggingFace accounts to viaSocket. Once connected, you can set up a workflow where an event in NileDesk triggers actions in HuggingFace (or vice versa).
Absolutely. You can customize how NileDesk 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 NileDesk 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 NileDesk 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 NileDesk
NileDesk is a Low-Code BPM software, empowering the staff in departments like HR, Finance, IT, Sales, Procurement, etc., to design efficient workflow solutions.
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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