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docs(compression): add MNIST compression tutorial (#3224)

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Add a comprehensive Jupyter notebook tutorial demonstrating TFLM's
compression pipeline using the MNIST dataset. The tutorial covers weight
clustering with TensorFlow Model Optimization toolkit, post-training
quantization, and TFLM's LUT-based compression.

Update documentation to reference the new tutorial from the main README,
Python interpreter guide, and compression documentation.

BUG=#2636

Co-authored-by: Esun Kim <veblush@google.com>
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Ryan Kuester 2025-10-17 12:01:13 -05:00 • committed by GitHub
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python/tflite_micro/README.md
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@ -157,6 +157,11 @@ print(tflm_interpreter.get_input_details(0))
print(tflm_interpreter.get_output_details(0))
```
### Tutorials
For a complete end-to-end example using the Python interpreter for model compression:
* [MNIST Compression Tutorial](../../tensorflow/lite/micro/compression/mnist_compression_tutorial.ipynb)
### Technical Details
The Python interpreter uses [pybind11](https://github.com/pybind/pybind11) to