Integrate OPENFORMAT and Hugging Face to automate workflows with scalable backend

Connect OPENFORMAT 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 OPENFORMAT and Hugging Face

Supported Triggers & Actions

OPENFORMAT NODES

Check Missions

Checks whether the user has completed all of the actions that make up a mission, and whether they have already been rewarded for completing the mission. [Full Documentation Here](https://docs.openformat.tech/no-code/buildship/nodes/check-missions)

Create web3 Account

Creates a web3 account for your user. You can learn more about what this is and how it benefits your users here.

Get Leaderboard

Returns a leaderboard based on the amount of experience points (XP) users have earned.

Get User Information

Returns the user's experience point (XP) balance, the badges they have collected and the actions they have completed within that specific dApp.

Reward Badge

Reward a user with a badge for completing an action or mission. [Full documentation here](https://docs.openformat.tech/no-code/buildship/nodes/reward-badge)

Reward XP

Reward a user with experience points (XP) for completing an action.

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

Recommended Reads

Below are recommneded blogs that will help in your journey