Integrate Leonardo AI and Hugging Face to automate workflows with scalable backend
Connect Leonardo 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 Leonardo AI and Hugging Face
Popular Templates With Leonardo AI and Hugging Face
Explore our popular Google Sheets & templates below. Click. Remix. Ship!
Node stack
Supported Triggers & Actions
Leonardo AI NODES
Generate Image
This endpoint generates images with the given generation prompt and returns the Generation ID.
Generate Prompt
This endpoint returns a random image generation prompt.
Improve Prompt
This endpoint returns an improved image generation prompt.
Upload Dataset Image
This endpoint uploads the given file buffer to the signed URL provided by the **Upload Init Image** node. Detailed instructions for using this endpoint are available in the guide: [How to upload an image using a presigned URL](https://docs.leonardo.ai/docs/how-to-upload-an-image-using-a-presigned-url).
Upload Init Image
This endpoint returns a random image generation prompt. Detailed instructions for using this endpoint are available in the guide: [How to upload an image using a presigned URL](https://docs.leonardo.ai/docs/how-to-upload-an-image-using-a-presigned-url).
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).
script
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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