diff --git a/pytorch_lightning/core/__init__.py b/pytorch_lightning/core/__init__.py
index c05f27e8d3..c29fea079f 100644
--- a/pytorch_lightning/core/__init__.py
+++ b/pytorch_lightning/core/__init__.py
@@ -94,7 +94,7 @@ Which you can train by doing:
     trainer = pl.Trainer()
     model = LitModel()
 
-   trainer.fit(model, train_loader)
+    trainer.fit(model, train_loader)
 
 ----------
 
diff --git a/pytorch_lightning/core/lightning.py b/pytorch_lightning/core/lightning.py
index 5ff64156e1..36b3ec3229 100644
--- a/pytorch_lightning/core/lightning.py
+++ b/pytorch_lightning/core/lightning.py
@@ -860,9 +860,9 @@ class LightningModule(ABC, DeviceDtypeModuleMixin, GradInformation, ModelIO, Mod
         Override to init DDP in your own way or with your own wrapper.
         The only requirements are that:
 
-        1. On a validation batch the call goes to ``model.validation_step``.
-        2. On a training batch the call goes to ``model.training_step``.
-        3. On a testing batch, the call goes to ``model.test_step``.+
+        1. On a validation batch, the call goes to ``model.validation_step``.
+        2. On a training batch, the call goes to ``model.training_step``.
+        3. On a testing batch, the call goes to ``model.test_step``.
 
         Args:
             model: the :class:`LightningModule` currently being optimized.