Update README.md

README.md

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 ## News
-- 🔥 uniGradICON [Slicer Extension](#-inferece-via-slicer-extension) is available in [3D Slicer](https://www.slicer.org/) 5.7.0 Extensions Manager (12/2024)
+- 🔥 uniGradICON [Slicer Extension](#-inference-via-slicer-extension) is available in [3D Slicer](https://www.slicer.org/) 5.7.0 Extensions Manager (12/2024)
 - 🏆 multiGradICON wins the best oral presentation at 2024 MICCAI Workshop for Biomedical Image Registration (WBIR) (10/2024)
 - 🔥 uniGradICON has been used as a baseline in [LUMIR Brain MRI Registration Challenge](https://github.com/JHU-MedImage-Reg/LUMIR_L2R) (6/2024)
 
 
 ## Introduction
 `uniGradICON` is based on [GradICON](https://github.com/uncbiag/ICON) but trained on several different datasets (see details below). 
-The result is a deep-learning-based registration model that works well across datasets. More results can be found [here](/demos/Examples.md). To get you started quickly there is also an easy to use [Slicer extension](#-inferece-via-slicer-extension). 
+The result is a deep-learning-based registration model that works well across datasets. More results can be found [here](/demos/Examples.md). To get you started quickly there is also an easy to use [Slicer extension](#-inference-via-slicer-extension). 
 
 <div align="center">
 <img src="IntroFigure.jpg" width=550 alt="teaser">
@@ -29,7 +29,7 @@ Demir, Basar and Tian, Lin and Greer, Thomas Hastings and Kwitt, Roland and Vial
 _MICCAI Workshop on Biomedical Image Registration (WBIR) 2024_ https://arxiv.org/abs/2408.00221  
 
 ## Easy to use and install
-The pre-trained uniGradICON and multiGradICON can be used via [CLI](#-inference-via-cli), [colab notebook](#-inferece-via-colab-notebook), and [Slicer Extension](#-inferece-via-slicer-extension). The model weights will be downloaded automatically. You can also find the model weights [here](https://github.com/uncbiag/uniGradICON/releases).
+The pre-trained uniGradICON and multiGradICON can be used via [CLI](#-inference-via-cli), [colab notebook](#-inference-via-colab-notebook), and [Slicer Extension](#-inference-via-slicer-extension). The model weights will be downloaded automatically. You can also find the model weights [here](https://github.com/uncbiag/uniGradICON/releases).
 
 ### 👉 Inference via CLI
 Installation