diff --git a/README.md b/README.md
index 7542eeef..91050f22 100644
--- a/README.md
+++ b/README.md
@@ -61,9 +61,9 @@ from torch.utils.data import DataLoader
 from torchvision.datasets import MNIST
 import torchvision.transforms as transforms
 
-import pytorch_lightning as ptl
+import pytorch_lightning as pl
 
-class CoolModel(ptl.LightningModule):
+class CoolModel(pl.LightningModule):
 
     def __init__(self):
         super(CoolModel, self).__init__()
@@ -93,15 +93,15 @@ class CoolModel(ptl.LightningModule):
     def configure_optimizers(self):
         return [torch.optim.Adam(self.parameters(), lr=0.02)]
 
-    @ptl.data_loader
+    @pl.data_loader
     def tng_dataloader(self):
         return DataLoader(MNIST(os.getcwd(), train=True, download=True, transform=transforms.ToTensor()), batch_size=32)
 
-    @ptl.data_loader
+    @pl.data_loader
     def val_dataloader(self):
         return DataLoader(MNIST(os.getcwd(), train=True, download=True, transform=transforms.ToTensor()), batch_size=32)
 
-    @ptl.data_loader
+    @pl.data_loader
     def test_dataloader(self):
         return DataLoader(MNIST(os.getcwd(), train=True, download=True, transform=transforms.ToTensor()), batch_size=32)
 ```
@@ -360,7 +360,7 @@ Nope! We use pure Pytorch everywhere and don't add unecessary abstractions!
 Nope.    
 
 ## Contributing    
-Welcome to the PTL community! We're building the most advanced research platform on the planet to implement the latest, best practices that the amazing PyTorch team rolls out!  
+Welcome to the PyTorch Lightning community! We're building the most advanced research platform on the planet to implement the latest, best practices that the amazing PyTorch team rolls out!  
 
 #### Bug fixes:  
 1. Submit a github issue.   
diff --git a/docs/LightningModule/RequiredTrainerInterface.md b/docs/LightningModule/RequiredTrainerInterface.md
index ace7829b..d0b5b6b3 100644
--- a/docs/LightningModule/RequiredTrainerInterface.md
+++ b/docs/LightningModule/RequiredTrainerInterface.md
@@ -36,9 +36,9 @@ from torch.utils.data import DataLoader
 from torchvision.datasets import MNIST
 import torchvision.transforms as transforms
 
-import pytorch_lightning as ptl
+import pytorch_lightning as pl
 
-class CoolModel(ptl.LightningModule):
+class CoolModel(pl.LightningModule):
 
     def __init__(self):
         super(CoolModel, self).__init__()
@@ -68,15 +68,15 @@ class CoolModel(ptl.LightningModule):
     def configure_optimizers(self):
         return [torch.optim.Adam(self.parameters(), lr=0.02)]
 
-    @ptl.data_loader
+    @pl.data_loader
     def tng_dataloader(self):
         return DataLoader(MNIST(os.getcwd(), train=True, download=True, transform=transforms.ToTensor()), batch_size=32)
 
-    @ptl.data_loader
+    @pl.data_loader
     def val_dataloader(self):
         return DataLoader(MNIST(os.getcwd(), train=True, download=True, transform=transforms.ToTensor()), batch_size=32)
 
-    @ptl.data_loader
+    @pl.data_loader
     def test_dataloader(self):
         return DataLoader(MNIST(os.getcwd(), train=True, download=True, transform=transforms.ToTensor()), batch_size=32)
 ```
@@ -303,10 +303,10 @@ def on_load_checkpoint(self, checkpoint):
 ### tng_dataloader 
 
 ``` {.python}
-@ptl.data_loader
+@pl.data_loader
 def tng_dataloader(self)
 ```
-Called by lightning during training loop. Make sure to use the @ptl.data_loader decorator, this ensures not calling this function until the data are needed.
+Called by lightning during training loop. Make sure to use the @pl.data_loader decorator, this ensures not calling this function until the data are needed.
 
 ##### Return
 PyTorch DataLoader
@@ -314,7 +314,7 @@ PyTorch DataLoader
 **Example**
 
 ``` {.python}
-@ptl.data_loader
+@pl.data_loader
 def tng_dataloader(self):
     transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (1.0,))])
     dataset = MNIST(root='/path/to/mnist/', train=True, transform=transform, download=True)
@@ -330,10 +330,10 @@ def tng_dataloader(self):
 ### val_dataloader 
 
 ``` {.python}
-@ptl.data_loader
+@pl.data_loader
 def tng_dataloader(self)
 ```
-Called by lightning during validation loop. Make sure to use the @ptl.data_loader decorator, this ensures not calling this function until the data are needed.
+Called by lightning during validation loop. Make sure to use the @pl.data_loader decorator, this ensures not calling this function until the data are needed.
 
 ##### Return
 PyTorch DataLoader
@@ -341,7 +341,7 @@ PyTorch DataLoader
 **Example**
 
 ``` {.python}
-@ptl.data_loader
+@pl.data_loader
 def val_dataloader(self):
     transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (1.0,))])
     dataset = MNIST(root='/path/to/mnist/', train=False, transform=transform, download=True)
@@ -358,10 +358,10 @@ def val_dataloader(self):
 ### test_dataloader 
 
 ``` {.python}
-@ptl.data_loader
+@pl.data_loader
 def test_dataloader(self)
 ```
-Called by lightning during test loop. Make sure to use the @ptl.data_loader decorator, this ensures not calling this function until the data are needed.
+Called by lightning during test loop. Make sure to use the @pl.data_loader decorator, this ensures not calling this function until the data are needed.
 
 ##### Return
 PyTorch DataLoader
@@ -369,7 +369,7 @@ PyTorch DataLoader
 **Example**
 
 ``` {.python}
-@ptl.data_loader
+@pl.data_loader
 def test_dataloader(self):
     transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (1.0,))])
     dataset = MNIST(root='/path/to/mnist/', train=False, transform=transform, download=True)
diff --git a/examples/new_project_templates/lightning_module_template.py b/examples/new_project_templates/lightning_module_template.py
index 483a4e3a..c2a0564f 100644
--- a/examples/new_project_templates/lightning_module_template.py
+++ b/examples/new_project_templates/lightning_module_template.py
@@ -13,7 +13,7 @@ from torch import optim
 from torch.utils.data import DataLoader
 from torch.utils.data.distributed import DistributedSampler
 
-import pytorch_lightning as ptl
+import pytorch_lightning as pl
 from pytorch_lightning.root_module.root_module import LightningModule
 
 
@@ -195,17 +195,17 @@ class LightningTemplateModel(LightningModule):
 
         return loader
 
-    @ptl.data_loader
+    @pl.data_loader
     def tng_dataloader(self):
         print('tng data loader called')
         return self.__dataloader(train=True)
 
-    @ptl.data_loader
+    @pl.data_loader
     def val_dataloader(self):
         print('val data loader called')
         return self.__dataloader(train=False)
 
-    @ptl.data_loader
+    @pl.data_loader
     def test_dataloader(self):
         print('test data loader called')
         return self.__dataloader(train=False)
diff --git a/tests/debug.py b/tests/debug.py
index 09e9186b..1ef9d54b 100644
--- a/tests/debug.py
+++ b/tests/debug.py
@@ -6,14 +6,14 @@ from pytorch_lightning.callbacks import ModelCheckpoint
 import os
 import shutil
 
-import pytorch_lightning as ptl
+import pytorch_lightning as pl
 import torch
 from torch.nn import functional as F
 from torch.utils.data import DataLoader
 from torchvision.datasets import MNIST
 
 
-class CoolModel(ptl.LightningModule):
+class CoolModel(pl.LightningModule):
 
     def __init(self):
         super(CoolModel, self).__init__()
@@ -43,15 +43,15 @@ class CoolModel(ptl.LightningModule):
     def configure_optimizers(self):
         return [torch.optim.Adam(self.parameters(), lr=0.02)]
 
-    @ptl.data_loader
+    @pl.data_loader
     def tng_dataloader(self):
         return DataLoader(MNIST('path/to/save', train=True), batch_size=32)
 
-    @ptl.data_loader
+    @pl.data_loader
     def val_dataloader(self):
         return DataLoader(MNIST('path/to/save', train=False), batch_size=32)
 
-    @ptl.data_loader
+    @pl.data_loader
     def test_dataloader(self):
         return DataLoader(MNIST('path/to/save', train=False), batch_size=32)