Integrate Hume AI and Hugging Face to automate workflows with scalable backend

Connect Hume AI and Hugging Face nodes to in your workflow. Integrate with any tool or database and ship powerful backend logic and APIs instantly - No code required!

Getting Started

How To Connect Hume AI and Hugging Face

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Step 1: Add Trigger Node

It is the node that will start your workflow execution.

Step 1: Add Trigger Node

It is the node that will start your workflow execution.

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Step 1: Add Trigger Node

It is the node that will start your workflow execution.

02

Step 2: Connect Hume AI and Hugging Face

It is the node that will start your workflow execution.

Step 2: Connect Hume AI and Hugging Face

It is the node that will start your workflow execution.

02

Step 2: Connect Hume AI and Hugging Face

It is the node that will start your workflow execution.

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Step 3: Integrate with any other tool or service

Add any other tools or your preferred database nodes. If an integration is not available generate your own using AI

Step 3: Integrate with any other tool or service

Add any other tools or your preferred database nodes. If an integration is not available generate your own using AI

03

Step 3: Integrate with any other tool or service

Add any other tools or your preferred database nodes. If an integration is not available generate your own using AI

04

Step 4: Execute Workflow

Once done, test and click ship to run as an API or scheduled job.

Step 4: Execute Workflow

Once done, test and click ship to run as an API or scheduled job.

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Step 4: Execute Workflow

Once done, test and click ship to run as an API or scheduled job.

Node stack

Supported Triggers & Actions

Hume AI NODES

Hugging Face NODES

Caption Image

Generate caption for the image using Hugging Face's [Salesforce/blip-image-captioning-large](https://huggingface.co/Salesforce/blip-image-captioning-large) model for image captioning pretrained on COCO dataset - base architecture (with ViT large backbone).

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Image Classification

Get classification labels for your image using Hugging Face's [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) model which is a transformer encoder model (BERT-like) pretrained on a large collection of images in a supervised fashion, namely ImageNet-21k, at a resolution of 224x224 pixels. Next, the model was fine-tuned on ImageNet (also referred to as ILSVRC2012), a dataset comprising 1 million images and 1,000 classes, also at resolution 224x224.

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Text Summarization

Summarize long text using Hugging Face's [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) model which is a transformer encoder-encoder (seq2seq) model with a bidirectional (BERT-like) encoder and an autoregressive (GPT-like) decoder. BART is pre-trained by (1) corrupting text with an arbitrary noising function, and (2) learning a model to reconstruct the original text.

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Text-To-Image

Generate image from text, using Hugging Face's [openskyml/dalle-3-xl](https://huggingface.co/openskyml/dalle-3-xl) test model very similar to Dall•E 3.

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Text-To-Music

Generate music from text using Hugging Face's [facebook/musicgen-small](https://huggingface.co/facebook/musicgen-small) model capable of generating high-quality music samples conditioned on text descriptions or audio prompts.

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Blog posts & Tutorials

Recommended
Reads

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Support

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Start building your
BIGGEST ideas
in the *simplest* of ways.

Start building your
BIGGEST ideas
in the *simplest* of ways.

Start building your BIGGEST ideas in the *simplest* of ways.