diff --git a/README.md b/README.md
index fe708ca6ad..b0de78cd3b 100644
--- a/README.md
+++ b/README.md
@@ -54,6 +54,37 @@ pip install pytorch-lightning
 [![Watch the video](https://github.com/PyTorchLightning/pytorch-lightning/blob/master/docs/source/_images/general/tutorial_cover.png)](https://www.youtube.com/watch?v=QHww1JH7IDU)
 
 ## Demo
+Here's a minimal example without a validation or test loop.
+
+```python
+# this is just a plain nn.Module with some structure
+
+class MNISTModel(pl.LightningModule):
+
+    def __init__(self):
+        super(MNISTModel, self).__init__()
+        self.l1 = torch.nn.Linear(28 * 28, 10)
+
+    def forward(self, x):
+        return torch.relu(self.l1(x.view(x.size(0), -1)))
+
+    def training_step(self, batch, batch_nb):
+        x, y = batch
+        loss = F.cross_entropy(self(x), y)
+        tensorboard_logs = {'train_loss': loss}
+        return {'loss': loss, 'log': tensorboard_logs}
+
+    def configure_optimizers(self):
+        return torch.optim.Adam(self.parameters(), lr=0.02)
+
+# train!
+train_loader = DataLoader(MNIST(os.getcwd(), train=True, download=True, transform=transforms.ToTensor()), batch_size=32)
+
+mnist_model = MNISTModel()
+trainer = pl.Trainer(gpus=8, precision=16)    
+trainer.fit(mnist_model, train_loader) 
+```
+
 [MNIST, GAN, BERT, DQN on COLAB!](https://colab.research.google.com/drive/1F_RNcHzTfFuQf-LeKvSlud6x7jXYkG31#scrollTo=HOk9c4_35FKg)   
 [MNIST on TPUs](https://colab.research.google.com/drive/1-_LKx4HwAxl5M6xPJmqAAu444LTDQoa3)