🔧 TensorFlow Lite is a lightweight solution for deploying machine learning models on mobile and embedded devices. Here's a step-by-step guide to convert your TensorFlow model:

  1. Prepare Your Model
    Ensure your model is saved in SavedModel format or Keras H5 file.

    tensorflow_lite_conversion

  2. Quantize the Model (Optional)
    Reduce model size and improve performance using quantization.

    model_quantization
    🔧 [Learn more about quantization](/learn/tutorials/optimizing_tensorflow_models)

  3. Convert with TensorFlow Lite Converter
    Use the tflite_convert tool to generate the .tflite file.

    tensorflow_converter_tool

  4. Validate the Converted Model
    Test it on your target device to ensure compatibility.

    tensorflow_lite_validation

📌 Tip: For complex models, consider using TensorFlow Lite Micro for microcontroller deployment.
✨ Ready to optimize your model further? Check out our TensorFlow Optimization Guide.