HUGGINGFACE_DEPLOYMENT.md

🚀 Hugging Face Spaces Deployment Guide

This guide will help you deploy the Enhanced Concrete Creep Prediction app to Hugging Face Spaces.

📋 Prerequisites

1. Hugging Face Account: Create an account at huggingface.co
2. Git LFS: Install Git Large File Storage for handling model files
3. Git: Standard Git installation

🛠️ Deployment Steps

Step 1: Create a New Space

1. Go to Hugging Face Spaces
2. Click "Create new Space"
3. Configure your space:
   • Name: concrete-creep-prediction (or your preferred name)
   • License: MIT
   • SDK: Streamlit
   • Hardware: CPU Basic (free tier) or CPU Upgrade/GPU for better performance

Step 2: Clone Your New Space

git clone https://huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME
cd YOUR_SPACE_NAME

Step 3: Copy Files from Deploy Directory

Copy all files from the deploy/ directory to your cloned space:

# Copy all files from deploy directory
cp /path/to/your/deploy/* ./

# Ensure executable permissions
chmod +x start_app.sh

Step 4: Initialize Git LFS

git lfs install
git lfs track "*.pt"
git lfs track "*.pkl"

Step 5: Add and Commit Files

git add .
git commit -m "Initial deployment of Enhanced Concrete Creep Prediction app"
git push

📁 Required Files Structure

Your Hugging Face Space should contain:

your-space/
├── app.py                      # Main Streamlit app
├── lllm_model_all_token.py     # Model architecture
├── requirements.txt            # Dependencies
├── README.md                   # Space description (with metadata)
├── .gitattributes             # Git LFS configuration
├── best_llm_model-17.pt       # Primary model (LFS)
├── final_llm_model-5.pt       # Alternative model (LFS)
└── scalers/                   # Scaler files (LFS)
    ├── feature_scaler.pkl
    ├── creep_scaler.pkl
    └── time_values.pkl

⚙️ Configuration Files

requirements.txt

streamlit
pandas
numpy
torch
matplotlib
scikit-learn
pickle-mixin

.gitattributes

*.pt filter=lfs diff=lfs merge=lfs -text
*.pkl filter=lfs diff=lfs merge=lfs -text
*.bin filter=lfs diff=lfs merge=lfs -text
*.safetensors filter=lfs diff=lfs merge=lfs -text

README.md Header

---
title: Enhanced Concrete Creep Prediction
emoji: 🏗️
colorFrom: blue
colorTo: green
sdk: streamlit
sdk_version: 1.28.0
app_file: app.py
pinned: false
license: mit
---

🚨 Important Notes

File Size Considerations

• Model files (~12MB each) require Git LFS
• Total space size should be under Hugging Face limits
• Consider using CPU Basic for free deployment

Performance Optimization

• Remove unused model files if space is limited
• The app automatically detects available models
• CPU inference is sufficient for most use cases

Memory Management

• Hugging Face Spaces have memory limits
• The app is optimized for cloud deployment
• Consider reducing default time points if needed

🔧 Troubleshooting

Common Issues:

1. Git LFS Issues

   git lfs install
   git lfs migrate import --include="*.pt,*.pkl"
   

2. Build Failures

   • Check requirements.txt format
   • Ensure all files are properly committed
   • Verify Python package compatibility

3. Memory Errors

   • Upgrade to CPU Upgrade hardware
   • Reduce model complexity in app.py
   • Optimize batch sizes

4. Model Loading Errors

   • Verify Git LFS is working
   • Check file paths in app.py
   • Ensure proper file permissions

🎯 Optimization Tips

For Better Performance:

1. Upgrade Hardware: Consider CPU Upgrade or GPU for faster inference
2. Caching: Streamlit caching is already implemented
3. Model Selection: Keep only the best performing model file
4. Time Points: Limit default prediction range for faster response

For Reliability:

1. Error Handling: Comprehensive error handling is included
2. Fallbacks: Multiple model loading strategies
3. User Feedback: Clear status messages and warnings

📊 Monitoring

After deployment, monitor:

• Build Logs: Check for any deployment issues
• Runtime Logs: Monitor app performance
• User Feedback: Gather usage statistics
• Resource Usage: Track memory and compute usage

🔄 Updates

To update your deployed app:

# Make changes locally
git add .
git commit -m "Update: [description of changes]"
git push

Hugging Face Spaces will automatically rebuild and redeploy.

📞 Support

• Hugging Face Docs: huggingface.co/docs/hub/spaces
• Community: Hugging Face Discord and Forums
• Issues: Create issues in your space repository

---

Ready to Deploy! 🚀

Your Enhanced Concrete Creep Prediction app will be available at: https://huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME