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
Popular Templates With Stripe and Hugging Face
Explore our popular Google Sheets & templates below. Click. Remix. Ship!
Node stack
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
Below are recommneded blogs that will help in your journey
Support
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