docs: Resolve many typos in the English docs (#20088)

* docs: Fix typo in ONNX parser help: 'tolerence' => 'tolerance'

* docs: Resolve many typos in the English docs

Typos found via 'codespell ./docs/source/en'

docs/source/en/model_doc/mobilevit.mdx

@@ -26,7 +26,7 @@ Tips:
 - One can use [`MobileViTFeatureExtractor`] to prepare images for the model. Note that if you do your own preprocessing, the pretrained checkpoints expect images to be in BGR pixel order (not RGB).
 - The available image classification checkpoints are pre-trained on [ImageNet-1k](https://huggingface.co/datasets/imagenet-1k) (also referred to as ILSVRC 2012, a collection of 1.3 million images and 1,000 classes).
 - The segmentation model uses a [DeepLabV3](https://arxiv.org/abs/1706.05587) head. The available semantic segmentation checkpoints are pre-trained on [PASCAL VOC](http://host.robots.ox.ac.uk/pascal/VOC/). 
-- As the name suggests MobileViT was desgined to be performant and efficient on mobile phones. The TensorFlow versions of the MobileViT models are fully compatible with [TensorFlow Lite](https://www.tensorflow.org/lite). 
+- As the name suggests MobileViT was designed to be performant and efficient on mobile phones. The TensorFlow versions of the MobileViT models are fully compatible with [TensorFlow Lite](https://www.tensorflow.org/lite). 
 
   You can use the following code to convert a MobileViT checkpoint (be it image classification or semantic segmentation) to generate a 
   TensorFlow Lite model: