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--- |
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title: Architech - AI Model Architect |
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emoji: 🏗️ |
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colorFrom: blue |
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colorTo: purple |
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sdk: gradio |
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sdk_version: 6.4.0 |
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app_file: app.py |
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pinned: false |
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license: mit |
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--- |
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# 🏗️ Architech - Your Personal AI Model Architect |
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**Create custom AI models without the headache!** Just describe what you want, and Architech handles the rest. |
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## ✨ Features |
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### 📊 Synthetic Data Generation |
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- Generate high-quality training data from simple descriptions |
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- Support for multiple domains: Technology, Healthcare, Finance, Education |
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- Multiple format types: Conversational, Instruction-following |
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- 50-500 examples per dataset |
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### 🚀 Model Training |
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- Fine-tune state-of-the-art models (GPT-2, DialoGPT) |
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- Automatic optimization and parameter tuning |
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- Direct deployment to HuggingFace Hub |
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- GPU-accelerated training with efficient memory usage |
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### 🧪 Model Testing |
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- Load and test your trained models instantly |
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- Interactive inference with adjustable parameters |
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- Real-time generation with temperature and length controls |
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### 🔒 Security & Limits |
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- **Rate Limiting**: Fair usage for all users |
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- Dataset Generation: 10/hour |
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- Model Training: 3/hour |
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- Model Inference: 50/hour |
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- **Token Authentication**: Secure HuggingFace integration |
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- **Error Handling**: Comprehensive error messages and recovery |
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## 🚀 Quick Start |
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### 1. Generate Training Data |
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1. Go to the **"Generate Dataset"** tab |
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2. Describe your task (e.g., "Customer support chatbot for tech products") |
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3. Select domain and size |
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4. Click **"Generate Dataset"** |
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### 2. Train Your Model |
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1. Go to the **"Train Model"** tab |
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2. Enter your model name and HuggingFace token |
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3. Choose to use synthetic data or provide your own |
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4. Click **"Train Model"** |
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5. Wait for training to complete (5-15 minutes) |
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### 3. Test Your Model |
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1. Go to the **"Test Model"** tab |
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2. Enter your model name and token |
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3. Click **"Load Model"** |
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4. Enter a test prompt and generate! |
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## 📋 Requirements |
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- HuggingFace account with **write** token |
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- For training: GPU recommended (CPU works but slower) |
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- Patience during training (coffee break recommended ☕) |
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## 🎯 Use Cases |
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- **Customer Support Bots**: Train chatbots for specific products/services |
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- **Content Generation**: Create domain-specific text generators |
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- **Educational Tools**: Build tutoring and explanation systems |
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- **Creative Writing**: Fine-tune for specific writing styles |
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- **Technical Documentation**: Generate code explanations and docs |
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## ⚙️ Technical Details |
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### Supported Base Models |
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- `distilgpt2` (fastest, smallest) |
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- `gpt2` (balanced) |
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- `microsoft/DialoGPT-small` (conversational) |
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### Training Features |
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- Gradient accumulation for memory efficiency |
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- Mixed precision training (FP16) |
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- Automatic learning rate optimization |
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- Smart tokenization and padding |
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### Synthetic Data Quality |
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- Domain-specific vocabulary |
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- Natural language variations |
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- Contextually relevant examples |
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- Edge case handling |
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## 🛠️ Troubleshooting |
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### "GPU Memory Overflow" |
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- Reduce batch size to 1 |
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- Use smaller base model (distilgpt2) |
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- Reduce dataset size |
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### "Permission Denied" |
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- Check your HuggingFace token has **WRITE** access |
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- Generate new token at: https://huggingface.co/settings/tokens |
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### "Rate Limit Exceeded" |
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- Wait for the cooldown period |
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- Check remaining requests in error message |
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## 📚 Best Practices |
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1. **Start Small**: Begin with 100 examples and 3 epochs |
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2. **Be Specific**: Detailed task descriptions yield better results |
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3. **Test First**: Use the Test tab before deploying |
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4. **Iterate**: Train multiple versions with different parameters |
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5. **Monitor**: Watch training logs for issues |
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## 🤝 Contributing |
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Found a bug? Have a feature request? Open an issue! |
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## 📜 License |
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MIT License - feel free to use and modify! |
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## 🙏 Acknowledgments |
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Built with: |
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- [Gradio](https://gradio.app/) - Interface |
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- [Transformers](https://huggingface.co/transformers/) - Models |
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- [HuggingFace](https://huggingface.co/) - Infrastructure |
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--- |
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*No PhD required. Just ideas.* ✨ |
