The TensorFlow Lite Converter is a tool that allows you to convert standard TensorFlow models into TensorFlow Lite format, enabling efficient deployment on mobile and embedded devices. 🛠️

Key Features 🔍

  • Model Optimization: Reduces model size and improves inference speed
  • Supported Formats:
    • ✅ TensorFlow SavedModel
    • ✅ TensorFlow HDF5
    • ✅ ONNX (via --input_format=onnx)
  • Converter Flags:
    • --output_type (e.g., float16, int8)
    • --target_ops (e.g., SELECTED, FULL)
    • --legalize for quantization compatibility

Usage Scenarios 🌐

  • Deploying ML models on Android/iOS apps
  • Running inference on microcontrollers (e.g., Raspberry Pi)
  • Integrating with TensorFlow Lite Micro for ultra-low resource environments

Conversion Steps 🔄

  1. Install the converter: 
    pip install tflite-converter
  2. Run the conversion: 
    tflite_convert --input_model=model.h5 --output_file=model.tflite
  3. Validate the output:
    TensorFlow_Lite_Converter_Validation

Best Practices 📌

  • Use --optimizations to enable graph optimizations
  • Test quantization with --input_type=int8 before deployment
  • Refer to our TensorFlow Lite Tutorials for hands-on examples

For advanced customization, explore the Converter API Reference to fine-tune conversion settings. 🧠