Integrate Hugging Face and Google Cloud Storage
Connect Hugging Face and Google Cloud Storage nodes in your workflow. Integrate with any tool or database and ship powerful backend logic and APIs instantly - No code required!
Node stack
Supported Hugging Face and Google Cloud Storage Nodes
Add any other tools or your preferred database nodes. If an integration is not available generate your own using AI
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).
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.
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.
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.
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.
Create File
Create a file with the given content, creating the folder if it doesn't exist
Delete File
Checks if a file exists in your GCP storage bucket and deletes it
Delete GCP Folder
Deletes a folder in GCP Storage if it exists
File Rename
Checks if a file exists at a given path in GCP storage and renames it
Generate Public Download URL
Generate a publicly accessible download URL from a Google Cloud Storage file path.
List GCP Storage Files
List files in the specified GCP storage bucket directory
Move File
Checks if a file exists in the Google Cloud Storage and if it does, moves it to a different location.
Move Folder
Check if a folder exists in the GCP storage and move it along with its contents to a different path.
Rename GCP Folder
Renames a given folder in Google Cloud Storage if it exists.
Upload Base64 File
Uploads a Base64 file to Google Cloud Storage and returns the public URL
Upload File from External URL
Uploads a file from an external URL to GCP Storage and returns its public URL
Upload Text to File
Uploads a text content to a specified GCP storage bucket and returns the file's public URL
Zip GCP Folder
Zips an existing folder in GCP storage and returns a download url.
Quick start
How to integrate Hugging Face and Google Cloud Storage
Step 1 — Add the nodes to your workflow
Create a new workflow in BuildShip, click “Add node”, and select the Hugging Face and Google Cloud Storage actions you want to use.
Step 2 — Configure each node
Go to each node to authenticate (or add your API key) and fill in the required parameters.
Step 3 — Connect the nodes
Each node in BuildShip can connect to others by using their output variables. When you reference a variable from one node in another, BuildShip automatically links them in the workflow.
Step 4 — Test your workflow
Define your starting data in the Inputs node and choose what to do with the result in the Flow Output node. Finally, run a test to see your workflow in action.
blog posts & tutorials
Recommended Reads
Below are recommneded blogs that will help in your journey
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