Integrate Stripe and Hugging Face to automate workflows with scalable backend

Connect Stripe 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 Stripe and Hugging Face

Supported Triggers & Actions

Stripe NODES

Stripe Webhook

Connect with your Stripe account and activates a workflow in response to specific webhook events. [Full documentation](https://docs.buildship.com/stripe)

Checkout Session: Customer Details

Returns the customer details from the stripe checkout session.

Checkout Session: Line Items

Returns the line items from a stripe checkout session.

Create Stripe Checkout Session

Create a Stripe checkout session and return the URL

Create Stripe Customer

Create a new customer on Stripe

Fetch Stripe Customer

Fetch a customer's data from Stripe

Get Stripe Event Metadata

Returns the metadata object associated with the Stripe event. Metadata is useful for storing additional, structured information on an object. For example, customer ID, subscription ID, etc.

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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