DeHug
Developer Documentation

Build with
DeHug

Complete documentation for integrating decentralized AI models and datasets into your applications. Start building the future of AI today.

Get Started in Minutes

Follow these simple steps to start using DeHug in your projects

Step 1
Install DeHug SDK
Get started with our Python SDK for seamless integration
pip install dehug
Step 2
Load a Model
Access any model from our decentralized repository
from dehug import DeHugRepository

model = DeHugRepository.load_model("Your model hash")
Step 3
Load a Dataset
Access training data stored on IPFS
dataset = DeHugRepository.load_dataset("Your dataset hash")
train_data = dataset["train"]
Step 4
Upload & Earn
Upload your own models/datasets and mint NFTs
nft_id = DeHugRepository.upload_model(
    model_path="./my-model",
    model_card="README.md"
)
Installation
Install the DeHug SDK using pip or conda

Using pip:

pip install dehug

Using conda:

conda install -c dehug dehug

Development version:

pip install git+https://github.com/dehug/dehug.git

Need Help?

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