Integrate Google Cloud and Hugging Face to automate workflows with scalable backend
Connect Google Cloud 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 Google Cloud and Hugging Face
Popular Templates With Google Cloud and Hugging Face
Explore our popular Google Sheets & templates below. Click. Remix. Ship!
Node stack
Supported Triggers & Actions
Google Cloud NODES
Get Secret
Retrieve a secret from Google Cloud Secret Manager
Google Cloud Text To Speech
Converts text to speech using Google Cloud Text to Speech API. ___ You must first [enable the Speech-to-Text API](https://console.cloud.google.com/apis/library/texttospeech.googleapis.com?project=_&supportedpurview=project) to use this node.
Google Vision Dominant Colors
Use Google Vision to detect the dominant colors in the given image.
Google Vision Text Detection
Detects text in an image using Google Cloud Vision API
PaLM API - Chat
Generates text in a conversational format using Google's Generative Language AI
Speech to Text
Converts speech to text using Google Cloud Speech-to-Text API. ___ You must first [enable the Speech-to-Text API](https://console.cloud.google.com/apis/library/texttospeech.googleapis.com?project=_&supportedpurview=project) to use this node.
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.
script
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.
script
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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