[Docs] Fix spelling and grammar mistakes (#28825)
* Fix typos and grammar mistakes in docs and examples * Fix typos in docstrings and comments * Fix spelling of `tokenizer` in model tests * Remove erroneous spaces in decorators * Remove extra spaces in Markdown link texts
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@@ -39,7 +39,7 @@ This model was contributed by [francesco](https://huggingface.co/francesco). The
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## Usage tips
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- MaskFormer's Transformer decoder is identical to the decoder of [DETR](detr). During training, the authors of DETR did find it helpful to use auxiliary losses in the decoder, especially to help the model output the correct number of objects of each class. If you set the parameter `use_auxilary_loss` of [`MaskFormerConfig`] to `True`, then prediction feedforward neural networks and Hungarian losses are added after each decoder layer (with the FFNs sharing parameters).
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- MaskFormer's Transformer decoder is identical to the decoder of [DETR](detr). During training, the authors of DETR did find it helpful to use auxiliary losses in the decoder, especially to help the model output the correct number of objects of each class. If you set the parameter `use_auxiliary_loss` of [`MaskFormerConfig`] to `True`, then prediction feedforward neural networks and Hungarian losses are added after each decoder layer (with the FFNs sharing parameters).
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- If you want to train the model in a distributed environment across multiple nodes, then one should update the
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`get_num_masks` function inside in the `MaskFormerLoss` class of `modeling_maskformer.py`. When training on multiple nodes, this should be
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set to the average number of target masks across all nodes, as can be seen in the original implementation [here](https://github.com/facebookresearch/MaskFormer/blob/da3e60d85fdeedcb31476b5edd7d328826ce56cc/mask_former/modeling/criterion.py#L169).
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