breast-cancer-africa-adjusted-dataset / upload_instructions.md
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Initial upload: African physiognomy-adjusted breast cancer dataset
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# 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