[docs] add the missing huggingface hub username (#33431)

* add username

* update username

* add username

docs/source/en/tasks/translation.md

@@ -346,7 +346,7 @@ The simplest way to try out your finetuned model for inference is to use it in a
 # Change `xx` to the language of the input and `yy` to the language of the desired output.
 # Examples: "en" for English, "fr" for French, "de" for German, "es" for Spanish, "zh" for Chinese, etc; translation_en_to_fr translates English to French
 # You can view all the lists of languages here - https://huggingface.co/languages
->>> translator = pipeline("translation_xx_to_yy", model="my_awesome_opus_books_model")
+>>> translator = pipeline("translation_xx_to_yy", model="username/my_awesome_opus_books_model")
 >>> translator(text)
 [{'translation_text': 'Legumes partagent des ressources avec des bactéries azotantes.'}]
 ```
@@ -360,7 +360,7 @@ Tokenize the text and return the `input_ids` as PyTorch tensors:
 ```py
 >>> from transformers import AutoTokenizer
 
->>> tokenizer = AutoTokenizer.from_pretrained("my_awesome_opus_books_model")
+>>> tokenizer = AutoTokenizer.from_pretrained("username/my_awesome_opus_books_model")
 >>> inputs = tokenizer(text, return_tensors="pt").input_ids
 ```
 
@@ -369,7 +369,7 @@ Use the [`~generation.GenerationMixin.generate`] method to create the translatio
 ```py
 >>> from transformers import AutoModelForSeq2SeqLM
 
->>> model = AutoModelForSeq2SeqLM.from_pretrained("my_awesome_opus_books_model")
+>>> model = AutoModelForSeq2SeqLM.from_pretrained("username/my_awesome_opus_books_model")
 >>> outputs = model.generate(inputs, max_new_tokens=40, do_sample=True, top_k=30, top_p=0.95)
 ```
 
@@ -386,7 +386,7 @@ Tokenize the text and return the `input_ids` as TensorFlow tensors:
 ```py
 >>> from transformers import AutoTokenizer
 
->>> tokenizer = AutoTokenizer.from_pretrained("my_awesome_opus_books_model")
+>>> tokenizer = AutoTokenizer.from_pretrained("username/my_awesome_opus_books_model")
 >>> inputs = tokenizer(text, return_tensors="tf").input_ids
 ```
 
@@ -395,7 +395,7 @@ Use the [`~transformers.generation_tf_utils.TFGenerationMixin.generate`] method
 ```py
 >>> from transformers import TFAutoModelForSeq2SeqLM
 
->>> model = TFAutoModelForSeq2SeqLM.from_pretrained("my_awesome_opus_books_model")
+>>> model = TFAutoModelForSeq2SeqLM.from_pretrained("username/my_awesome_opus_books_model")
 >>> outputs = model.generate(inputs, max_new_tokens=40, do_sample=True, top_k=30, top_p=0.95)
 ```