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Migrate Model Maker tutorials to tf.org/lite
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‎tensorflow_examples/lite/model_maker/README.md‎

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For instance, it could have an end-to-end image classification example that
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utilizes this library with just 4 lines of code, each of which representing one
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step of the overall process. For more detail, you could refer to
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[Colab for image classification](https://colab.research.google.com/github/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/demo/image_classification.ipynb).
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[Colab for image classification](https://colab.research.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/tutorials/model_maker_image_classification.ipynb).
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1. Load input data specific to an on-device ML app.
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Currently, we support image classification and text classification tasks and
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provide demo code and colab for each of them in demo folder.
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* [Colab for image classification](https://colab.research.google.com/github/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/demo/image_classification.ipynb)
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* [Colab for text classification](https://colab.research.google.com/github/tensorflow/examples/blob/master/tensorflow_examples/lite/model_maker/demo/text_classification.ipynb)
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* [Colab for image classification](https://colab.research.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/tutorials/model_maker_image_classification.ipynb)
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* [Colab for text classification](https://colab.research.google.com/github/tensorflow/tensorflow/blob/master/tensorflow/lite/g3doc/tutorials/model_maker_text_classification.ipynb)

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