Update all references to canonical models (#29001)

* Script & Manual edition

* Update

docs/source/en/main_classes/output.md

@@ -26,8 +26,8 @@ Let's see how this looks in an example:
 from transformers import BertTokenizer, BertForSequenceClassification
 import torch
 
-tokenizer = BertTokenizer.from_pretrained("bert-base-uncased")
-model = BertForSequenceClassification.from_pretrained("bert-base-uncased")
+tokenizer = BertTokenizer.from_pretrained("google-bert/bert-base-uncased")
+model = BertForSequenceClassification.from_pretrained("google-bert/bert-base-uncased")
 
 inputs = tokenizer("Hello, my dog is cute", return_tensors="pt")
 labels = torch.tensor([1]).unsqueeze(0)  # Batch size 1

docs/source/en/main_classes/pipelines.md

@@ -43,7 +43,7 @@ If you want to use a specific model from the [hub](https://huggingface.co) you c
 the hub already defines it:
 
 ```python
->>> pipe = pipeline(model="roberta-large-mnli")
+>>> pipe = pipeline(model="FacebookAI/roberta-large-mnli")
 >>> pipe("This restaurant is awesome")
 [{'label': 'NEUTRAL', 'score': 0.7313136458396912}]
 ```