# Hugging Face Dataset Upload Instructions

## Prerequisites

1. **Install Hugging Face Hub**:
```bash
pip install huggingface_hub
```

2. **Login to Hugging Face**:
```bash
huggingface-cli login
```
Enter your Hugging Face token when prompted.

## Upload Steps

### Option 1: Using Hugging Face Hub (Recommended)

```bash
# 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

```python
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

```python
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