Address reviewer comments

examples/multi-language/README.md

@@ -66,10 +66,16 @@ Please note that the Java pipeline is
 #### Setup
 
 * Obtain/generate a csv input file that contains labels and pixels to feed into the model and store it in
-GCS. And example input is available [here](TODO).
+GCS. An example input is available
+[here](https://storage.googleapis.com/apache-beam-samples/multi-language/mnist/example_input.csv).
 
 * Create a model file that contains the pickled file of a scikit-learn model
-trained on MNIST data and store it in GCS. An example model file is available [here](TODO).
+trained on MNIST data and store it in GCS. An example model file is available
+[here](https://storage.googleapis.com/apache-beam-samples/multi-language/mnist/example_model).
+This model was generated by by running the program given
+[here](https://python-course.eu/machine-learning/training-and-testing-with-mnist.php)
+on the
+[example input dataset](https://storage.googleapis.com/apache-beam-samples/multi-language/mnist/example_input.csv).
 
 * Perform Beam runner specific setup according to instructions
 [here](https://beam.apache.org/get-started/quickstart-java/#run-a-pipeline).
@@ -160,9 +166,3 @@ of the digit. The second item is the predicted label of the digit.
 ```
 gsutil cat gs://$GCP_BUCKET/multi-language-beam/output*
 ```
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