Update mnist-quickrun example and add a readme file.

examples/mnist_quickrun/readme.md

+# Demo training task : MNIST in Quickrun Mode
+
+## Overview
+
+**We are going to use the declearn-quickrun tool to easily run a simulated
+federated learning experiment on the classic
+[MNIST dataset](http://yann.lecun.com/exdb/mnist/)**. The input of the model
+is a set of images of handwritten digits, and the model needs to determine to
+which digit between $0$ and $9$ each image corresponds.
+
+## Setup
+
+A Jupyter Notebook tutorial is provided, that you may import and run on Google
+Colab so as to avoid having to set up a local python environment.
+
+Alternatively, you may run the notebook on your personal computer, or follow
+its instructions to install declearn and operate the quickrun tools directly
+from a shell command-line.
+
+## Contents
+
+This example's folder is structured the following way:
+
+```
+mnist/
+│    config.toml - configuration file for the quickrun FL experiment
+|    mnist.ipynb - tutorial for this example, as a jupyter notebook
+|    model.py    - python file declaring the model to be trained
+└─── data_iid    - mnist data generated with `declearn-split`
+└─── results_*   - results generated after running `declearn-quickrun`
+```