diff --git a/docs/source/add_new_pipeline.rst b/docs/source/add_new_pipeline.rst
index a49772fbd3d29..ccf587968f62c 100644
--- a/docs/source/add_new_pipeline.rst
+++ b/docs/source/add_new_pipeline.rst
@@ -29,23 +29,23 @@ Start by inheriting the base class :obj:`Pipeline`. with the 4 methods needed to
     from transformers import Pipeline
 
     class MyPipeline(Pipeline):
-        def _sanitize_parameters(self, **kwargs)
+        def _sanitize_parameters(self, **kwargs):
             preprocess_kwargs = {}
             if "maybe_arg" in kwargs:
                 preprocess_kwargs["maybe_arg"] = kwargs["maybe_arg"]
             return preprocess_kwargs, {}, {}
 
-        def preprocess(self, inputs, maybe_arg=2)
+        def preprocess(self, inputs, maybe_arg=2):
             model_input = Tensor(....)
             return {"model_input": model_input}
 
-        def _forward(self, model_inputs)
+        def _forward(self, model_inputs):
             # model_inputs == {"model_input": model_input}
-            oututs = self.model(**model_inputs)
+            outputs = self.model(**model_inputs)
             # Maybe {"logits": Tensor(...)}
             return outputs
 
-        def postprocess(self, model_outputs)
+        def postprocess(self, model_outputs):
             best_class = model_outputs["logits"].softmax(-1)
             return best_class
 
@@ -89,12 +89,12 @@ In order to achieve that, we'll update our :obj:`postprocess` method with a defa
 .. code-block::
 
 
-        def postprocess(self, model_outputs, top_k=5)
+        def postprocess(self, model_outputs, top_k=5):
             best_class = model_outputs["logits"].softmax(-1)
             # Add logic to handle top_k
             return best_class
 
-        def _sanitize_parameters(self, **kwargs)
+        def _sanitize_parameters(self, **kwargs):
             preprocess_kwargs = {}
             if "maybe_arg" in kwargs:
                 preprocess_kwargs["maybe_arg"] = kwargs["maybe_arg"]