diff --git a/examples/mnist-pytorch/README.rst b/examples/mnist-pytorch/README.rst index 231a8310c..63a686664 100644 --- a/examples/mnist-pytorch/README.rst +++ b/examples/mnist-pytorch/README.rst @@ -1,5 +1,5 @@ Quickstart Tutorial PyTorch (MNIST) -------------- +------------------------------------- This classic example of hand-written text recognition is well suited as a lightweight test when developing on FEDn in pseudo-distributed mode. A normal high-end laptop or a workstation should be able to sustain a few clients. @@ -112,8 +112,8 @@ You are now ready to use the API to initialize the system with the compute packa - Follow the example in the `Jupyter Notebook `__ -Automate experimentation with several clients: ------------ +Automate experimentation with several clients +----------------------------------------------- Now that you have an understanding of the main components of FEDn, you can use the provided docker-compose templates to automate deployment of FEDn and clients. To start the network and attach 4 clients: @@ -124,7 +124,7 @@ To start the network and attach 4 clients: Access logs and validation data from MongoDB ------------ +--------------------------------------------- You can access and download event logs and validation data via the API, and you can also as a developer obtain the MongoDB backend data using pymongo or via the MongoExpress interface: @@ -133,7 +133,7 @@ the MongoDB backend data using pymongo or via the MongoExpress interface: The credentials are as set in docker-compose.yaml in the root of the repository. Access model updates ------------ +--------------------- You can obtain model updates from the 'fedn-models' bucket in Minio: