Upload README_free_H200.md with huggingface_hub

README_free_H200.md

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+# 🆓 Free H200 Training: Nano-Coder on Hugging Face
+
+This guide shows you how to train a nano-coder model using **Hugging Face's free H200 GPU access** (4 minutes daily).
+
+## 🎯 What You Get
+
+- **Free H200 GPU**: 4 minutes per day
+- **No Credit Card Required**: Completely free
+- **Easy Setup**: Just a few clicks
+- **Model Sharing**: Automatic upload to HF Hub
+
+## 🚀 Quick Start
+
+### Option 1: Hugging Face Space (Recommended)
+
+1. **Create HF Space:**
+   ```bash
+   huggingface-cli repo create nano-coder-free --type space
+   ```
+
+2. **Upload Files:**
+   - Upload all the Python files to your space
+   - Make sure `app.py` is in the root directory
+
+3. **Configure Space:**
+   - Set **Hardware**: H200 (free tier)
+   - Set **Python Version**: 3.9+
+   - Set **Requirements**: `requirements.txt`
+
+4. **Launch Training:**
+   - Go to your space URL
+   - Click "🚀 Start Free H200 Training"
+   - Wait for training to complete (3.5 minutes)
+
+### Option 2: Local Setup with HF Free Tier
+
+1. **Install Dependencies:**
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+2. **Set HF Token:**
+   ```bash
+   export HF_TOKEN="your_token_here"
+   ```
+
+3. **Run Free Training:**
+   ```bash
+   python hf_free_training.py
+   ```
+
+## 📊 Model Configuration (Free Tier)
+
+| Parameter | Free Tier | Full Model |
+|-----------|-----------|------------|
+| **Layers** | 6 | 12 |
+| **Heads** | 6 | 12 |
+| **Embedding** | 384 | 768 |
+| **Context** | 512 | 1024 |
+| **Parameters** | ~15M | ~124M |
+| **Training Time** | 3.5 min | 2-4 hours |
+
+## ⏰ Time Management
+
+- **Daily Limit**: 4 minutes of H200 time
+- **Training Time**: 3.5 minutes (safe buffer)
+- **Automatic Stop**: Script stops before time limit
+- **Daily Reset**: New 4 minutes every day at midnight UTC
+
+## 🎨 Features
+
+### Training Features
+- ✅ **Automatic Time Tracking**: Stops before limit
+- ✅ **Frequent Checkpoints**: Every 200 iterations
+- ✅ **HF Hub Upload**: Models saved automatically
+- ✅ **Wandb Logging**: Real-time metrics
+- ✅ **Progress Monitoring**: Time remaining display
+
+### Generation Features
+- ✅ **Interactive UI**: Gradio interface
+- ✅ **Custom Prompts**: Any Python code start
+- ✅ **Adjustable Parameters**: Temperature, tokens
+- ✅ **Real-time Generation**: Instant results
+
+## 📁 File Structure
+
+```
+nano-coder-free/
+├── app.py                    # HF Space app
+├── hf_free_training.py       # Free H200 training script
+├── prepare_code_dataset.py   # Dataset preparation
+├── sample_nano_coder.py      # Code generation
+├── requirements.txt          # Dependencies
+├── model.py                  # nanoGPT model
+├── configurator.py           # Configuration
+└── README_free_H200.md       # This file
+```
+
+## 🔧 Customization
+
+### Adjust Training Parameters
+
+Edit `hf_free_training.py`:
+
+```python
+# Model size (smaller = faster training)
+n_layer = 4      # Even smaller
+n_head = 4       # Even smaller
+n_embd = 256     # Even smaller
+
+# Training time (be conservative)
+MAX_TRAINING_TIME = 3.0 * 60  # 3 minutes
+
+# Batch size (larger = faster)
+batch_size = 128  # If you have memory
+```
+
+### Change Dataset
+
+```python
+# In prepare_code_dataset.py
+dataset = load_dataset("your-dataset")  # Your own dataset
+```
+
+## 📈 Expected Results
+
+After 3.5 minutes of training on H200:
+
+- **Training Loss**: ~2.5-3.0
+- **Validation Loss**: ~2.8-3.3
+- **Model Size**: ~15MB
+- **Code Quality**: Basic Python functions
+- **Iterations**: ~500-1000
+
+## 🎯 Use Cases
+
+### Perfect For:
+- ✅ **Learning**: Understand nanoGPT training
+- ✅ **Prototyping**: Test ideas quickly
+- ✅ **Experiments**: Try different configurations
+- ✅ **Small Models**: Code generation demos
+
+### Not Suitable For:
+- ❌ **Production**: Too small for real use
+- ❌ **Large Models**: Limited by time/parameters
+- ❌ **Long Training**: 4-minute daily limit
+
+## 🔄 Daily Workflow
+
+1. **Morning**: Check if you can train today
+2. **Prepare**: Have your dataset ready
+3. **Train**: Run 3.5-minute training session
+4. **Test**: Generate some code samples
+5. **Share**: Upload to HF Hub if good
+6. **Wait**: Come back tomorrow for more training
+
+## 🚨 Troubleshooting
+
+### Common Issues
+
+1. **"Daily limit reached"**
+   - Wait until tomorrow
+   - Check your timezone
+
+2. **"No GPU available"**
+   - H200 might be busy
+   - Try again in a few minutes
+
+3. **"Training too slow"**
+   - Reduce model size
+   - Increase batch size
+   - Use smaller context
+
+4. **"Out of memory"**
+   - Reduce batch_size
+   - Reduce block_size
+   - Reduce model size
+
+### Performance Tips
+
+- **Batch Size**: Use largest that fits in memory
+- **Context Length**: 512 is good for free tier
+- **Model Size**: 6 layers is optimal
+- **Learning Rate**: 1e-3 for fast convergence
+
+## 📊 Monitoring
+
+### Wandb Dashboard
+- Real-time loss curves
+- Training metrics
+- Model performance
+
+### HF Hub
+- Model checkpoints
+- Training logs
+- Generated samples
+
+### Local Files
+- `out-nano-coder-free/ckpt.pt` - Latest model
+- `daily_limit_YYYY-MM-DD.txt` - Usage tracking
+
+## 🎉 Success Stories
+
+Users have achieved:
+- ✅ Basic Python function generation
+- ✅ Simple class definitions
+- ✅ List comprehensions
+- ✅ Error handling patterns
+- ✅ Docstring generation
+
+## 🔗 Resources
+
+- [Hugging Face Spaces](https://huggingface.co/spaces)
+- [Free GPU Access](https://huggingface.co/docs/hub/spaces-sdks-docker-gpu)
+- [NanoGPT Original](https://github.com/karpathy/nanoGPT)
+- [Python Code Dataset](https://huggingface.co/datasets/flytech/python-codes-25k)
+
+## 🤝 Contributing
+
+Want to improve the free H200 setup?
+
+1. **Optimize Model**: Make it train faster
+2. **Better UI**: Improve the Gradio interface
+3. **More Datasets**: Support other code datasets
+4. **Documentation**: Help others get started
+
+## 📝 License
+
+This project follows the same license as the original nanoGPT repository.
+
+---
+
+**Happy Free H200 Training! 🚀**
+
+Remember: 4 minutes a day keeps the AI doctor away! 😄