Integrate Hugging Face and Firebase
Connect Hugging Face and Firebase 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 Firebase 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.
Firebase Auth Request
Authenticates Firebase user bearer token and add user info to context. [Full Documentation](https://docs.buildship.com/trigger-nodes/firebase-auth)
Rest API File Upload (Auth)
Create an API / HTTP endpoint to accept a file with multipart/form-data content type only from Firebase Authenticated users. Authentication is done by checking the bearer token in request header. NOTE: The trigger accepts only one file per request. [Full Documentation](https://docs.buildship.com/trigger-nodes/firebase-file-upload)
Create Firebase User
Create a new Firebase Auth User with email, full name, and password
Get User Data With Auth Token
Fetch user data from Firebase based on the auth token
Get User Data With ID
Fetch user data from Firebase Auth based given their user ID
Mark Firebase User as Verified
Mark a Firebase Auth User as verified using user id
User Exists Check
Checks if a firebase user already exists for the given email
Quick start
How to integrate Hugging Face and Firebase
Step 1 — Add the nodes to your workflow
Create a new workflow in BuildShip, click “Add node”, and select the Hugging Face and Firebase 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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