diff --git a/README.md b/README.md
index fd00bcaa6bd..c77320656fd 100644
--- a/README.md
+++ b/README.md
@@ -39,13 +39,15 @@ ______________________________________________________________________
 </div>
 
 # Looking for GPUs?
-Over 340,000 developers use [Lightning Cloud](https://lightning.ai/?utm_source=tm_readme&utm_medium=referral&utm_campaign=tm_readme) - purpose-built for PyTorch and PyTorch Lightning. 
-- [GPUs](https://lightning.ai/pricing?utm_source=tm_readme&utm_medium=referral&utm_campaign=tm_readme) from $0.19.   
-- [Clusters](https://lightning.ai/clusters?utm_source=tm_readme&utm_medium=referral&utm_campaign=tm_readme): frontier-grade training/inference clusters.   
+
+Over 340,000 developers use [Lightning Cloud](https://lightning.ai/?utm_source=tm_readme&utm_medium=referral&utm_campaign=tm_readme) - purpose-built for PyTorch and PyTorch Lightning.
+
+- [GPUs](https://lightning.ai/pricing?utm_source=tm_readme&utm_medium=referral&utm_campaign=tm_readme) from $0.19.
+- [Clusters](https://lightning.ai/clusters?utm_source=tm_readme&utm_medium=referral&utm_campaign=tm_readme): frontier-grade training/inference clusters.
 - [AI Studio (vibe train)](https://lightning.ai/studios?utm_source=tm_readme&utm_medium=referral&utm_campaign=tm_readme): workspaces where AI helps you debug, tune and vibe train.
-- [AI Studio (vibe deploy)](https://lightning.ai/studios?utm_source=tm_readme&utm_medium=referral&utm_campaign=tm_readme): workspaces where AI helps you optimize, and deploy models.     
+- [AI Studio (vibe deploy)](https://lightning.ai/studios?utm_source=tm_readme&utm_medium=referral&utm_campaign=tm_readme): workspaces where AI helps you optimize, and deploy models.
 - [Notebooks](https://lightning.ai/notebooks?utm_source=tm_readme&utm_medium=referral&utm_campaign=tm_readme): Persistent GPU workspaces where AI helps you code and analyze.
-- [Inference](https://lightning.ai/deploy?utm_source=tm_readme&utm_medium=referral&utm_campaign=tm_readme): Deploy models as inference APIs.   
+- [Inference](https://lightning.ai/deploy?utm_source=tm_readme&utm_medium=referral&utm_campaign=tm_readme): Deploy models as inference APIs.
 
 # Installation
 
diff --git a/src/torchmetrics/segmentation/dice.py b/src/torchmetrics/segmentation/dice.py
index 2723a2c3ebd..148dc2e15c2 100644
--- a/src/torchmetrics/segmentation/dice.py
+++ b/src/torchmetrics/segmentation/dice.py
@@ -73,8 +73,6 @@ class DiceScore(Metric):
         input_format: What kind of input the function receives.
             Choose between ``"one-hot"`` for one-hot encoded tensors, ``"index"`` for index tensors
             or ``"mixed"`` for one one-hot encoded and one index tensor
-        zero_division: The value to return when there is a division by zero. Options are 1.0, 0.0, "warn" or "nan".
-            Setting it to "warn" behaves like 0.0 but will also create a warning.
         kwargs: Additional keyword arguments, see :ref:`Metric kwargs` for more info.
 
     Raises: