Fix R vs S denoising documentation swap.
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README.md
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@@ -99,9 +99,9 @@ This model was contributed by [Daniel Hesslow](https://huggingface.co/Seledorn).
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The following shows how one can predict masked passages using the different denoising strategies.
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Given the size of the model the following examples need to be run on at least a 40GB A100 GPU.
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###
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For *
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```python
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from transformers import T5ForConditionalGeneration, AutoTokenizer
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@@ -120,9 +120,9 @@ print(tokenizer.decode(outputs[0]))
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# -> <pad>. Dudley was a very good boy, but he was also very stupid.</s>
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```
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###
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For *
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```python
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from transformers import T5ForConditionalGeneration, AutoTokenizer
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The following shows how one can predict masked passages using the different denoising strategies.
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Given the size of the model the following examples need to be run on at least a 40GB A100 GPU.
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### S-Denoising
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For *S-Denoising*, please make sure to prompt the text with the prefix `[S2S]` as shown below.
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```python
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from transformers import T5ForConditionalGeneration, AutoTokenizer
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# -> <pad>. Dudley was a very good boy, but he was also very stupid.</s>
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```
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### R-Denoising
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For *R-Denoising*, please make sure to prompt the text with the prefix `[NLU]` as shown below.
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```python
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from transformers import T5ForConditionalGeneration, AutoTokenizer
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