upload_instructions.md

Hugging Face Dataset Upload Instructions

Prerequisites

1. Install Hugging Face Hub:

pip install huggingface_hub

2. Login to Hugging Face:

huggingface-cli login

Enter your Hugging Face token when prompted.

Upload Steps

Option 1: Using Hugging Face Hub (Recommended)

# Navigate to the dataset folder
cd huggingface_dataset

# Initialize git repository
git init
git add .
git commit -m "Initial commit: African physiognomy-adjusted breast cancer dataset"

# Add Hugging Face remote (replace USERNAME with your HF username)
git remote add origin https://huggingface.co/datasets/USERNAME/breast-cancer-african-adjusted

# Push to Hugging Face
git push -u origin main

Option 2: Using Python Script

from huggingface_hub import HfApi, upload_folder

api = HfApi()

# Upload the entire folder
api.upload_folder(
    folder_path="huggingface_dataset",
    repo_id="USERNAME/breast-cancer-african-adjusted",  # Replace USERNAME
    repo_type="dataset",
    commit_message="Upload African physiognomy-adjusted breast cancer dataset"
)

Option 3: Web Interface

1. Go to https://huggingface.co/new-dataset
2. Create a new dataset repository: breast-cancer-african-adjusted
3. Upload files through the web interface:
   • README.md (dataset card)
   • breast_cancer_african_adjusted.csv
   • breast_cancer_original.csv
   • dataset_infos.json
   • breast_cancer_african_adjusted.py
   • .gitattributes

Dataset Repository Structure

USERNAME/breast-cancer-african-adjusted/
├── README.md                           # Dataset card with metadata
├── breast_cancer_african_adjusted.csv  # Main adjusted dataset
├── breast_cancer_original.csv          # Original Wisconsin dataset
├── dataset_infos.json                  # Dataset configuration
├── breast_cancer_african_adjusted.py   # Loading script
└── .gitattributes                      # Git LFS configuration

Post-Upload Checklist

• Verify dataset loads correctly: load_dataset("USERNAME/breast-cancer-african-adjusted")
• Check dataset card displays properly on Hugging Face
• Test both "african_adjusted" and "original" configurations
• Add appropriate tags and categories
• Set proper license (CC BY 4.0)
• Add to relevant collections (medical, healthcare-bias, etc.)

Usage After Upload

from datasets import load_dataset

# Load African-adjusted version (default)
dataset = load_dataset("USERNAME/breast-cancer-african-adjusted")

# Load original version
original_dataset = load_dataset("USERNAME/breast-cancer-african-adjusted", "original")

# Access the data
data = dataset['train']
print(f"Dataset size: {len(data)}")
print(f"Features: {data.features}")

Notes

• Replace USERNAME with your actual Hugging Face username
• Ensure you have the necessary permissions to upload datasets
• The dataset will be publicly available under CC BY 4.0 license
• Consider adding the dataset to relevant Hugging Face collections for discoverability