Integrate BuildShip File Storage and Hugging Face to automate workflows and backend

Connect BuildShip File Storage 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 BuildShip File Storage and Hugging Face

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Step 1: Add Trigger Node

It is the node that will start your workflow execution.

Step 1: Add Trigger Node

It is the node that will start your workflow execution.

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Step 1: Add Trigger Node

It is the node that will start your workflow execution.

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Step 2: Connect BuildShip File Storage and Hugging Face

It is the node that will start your workflow execution.

Step 2: Connect BuildShip File Storage and Hugging Face

It is the node that will start your workflow execution.

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Step 2: Connect BuildShip File Storage and Hugging Face

It is the node that will start your workflow execution.

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Step 3: Integrate with any other tool or service

Add any other tools or your preferred database nodes. If an integration is not available generate your own using AI

Step 3: Integrate with any other tool or service

Add any other tools or your preferred database nodes. If an integration is not available generate your own using AI

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Step 3: Integrate with any other tool or service

Add any other tools or your preferred database nodes. If an integration is not available generate your own using AI

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Step 4: Execute Workflow

Once done, test and click ship to run as an API or scheduled job.

Step 4: Execute Workflow

Once done, test and click ship to run as an API or scheduled job.

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Step 4: Execute Workflow

Once done, test and click ship to run as an API or scheduled job.

Node stack

Supported Triggers & Actions

BuildShip File Storage NODES

Delete File

Checks if a file exists in BuildShip's GCP storage and deletes it

Delete Folder

Deletes a folder in BuildShip's GCP Storage if it exists.

File Rename

Checks if a file exists at a given path in BuildShip's in-built GCP storage and renames it

Generate Public Download URL

Generate a publicly accessible download URL from BuildShip's Google Cloud Storage file path.

List Files

List files in BuildShip's GCP storage bucket directory

Move File

Checks if a file exists in BuildShip's GCP Storage and if it does, moves it to a different location.

Move Folder

Check if a folder exists in BuildShip's GCP storage and move it along with its contents to a different path.

Rename Storage Folder

Renames a given folder in BuildShip's GCP Storage if it exists.

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Upload Base64 File

Uploads a Base64 file to BuildShip's in-built Google Cloud Storage Bucket and returns the public URL

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Upload File

Uploads a file to BuildShip's in-built Google Cloud Storage Bucket and returns the public URL

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Upload File Buffer

Uploads a file from a buffer to BuildShip's in-built Google Cloud Storage Bucket and returns the public URL

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Upload File From URL

Uploads a file from URL to BuildShip's in-built Google Cloud Storage Bucket and returns the public URL

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Upload Text to File

Uploads a text content to the in-built BuildShip GCP storage bucket and returns the file's public URL.

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Zip Folder

Zips an existing folder in BuildShip's GCP storage and returns a download url.

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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

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in the *simplest* of ways.

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