Deploying AI Models with AI Toolkit 🛠️

Step-by-Step Guide to Deploy Your AI Model

1. Prepare Your Environment

   • Install the AI Toolkit via npm or pip
   • Set up a virtual environment for isolation 🌐
   • Ensure dependencies are met with npm install or pip install -r requirements.txt

2. Configure Your Model

   • Load your trained model using the AI Toolkit API 📁
   • Define input/output formats in config.yaml
   • Example:

     model_path: "models/my_model.pth"
     input_shape: [224, 224]
     

3. Deploy the Service

   • Use the built-in server: ai_toolkit serve
   • Or containerize with Docker for scalability 🐳
   • Access the endpoint at http://localhost:8080/api/predict

4. Test & Monitor

   • Send test requests via Postman or curl 📈
   • Monitor performance using the AI Toolkit Dashboard
   • Check logs in logs/deployment.log

Advanced Tips

• For production, use Kubernetes for orchestration 🔄
• Optimize model latency with TensorRT integration 🚀

Explore more deployment options or view the documentation center for detailed guides.