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Fix doc examples #8082

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Merged
sgugger merged 1 commit into from
Oct 27, 2020
Merged

Fix doc examples #8082

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14 changes: 7 additions & 7 deletions src/transformers/file_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -651,7 +651,7 @@ def _prepare_output_docstrings(output_type, config_class):
>>> import tensorflow as tf

>>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}')
>>> model = {model_class}.from_pretrained('{checkpoint}', return_dict=True))
>>> model = {model_class}.from_pretrained('{checkpoint}', return_dict=True)

>>> inputs = tokenizer("Hello, my dog is cute", return_tensors="tf")
>>> input_ids = inputs["input_ids"]
Expand All @@ -669,7 +669,7 @@ def _prepare_output_docstrings(output_type, config_class):
>>> import tensorflow as tf

>>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}')
>>> model = {model_class}.from_pretrained('{checkpoint}', return_dict=True))
>>> model = {model_class}.from_pretrained('{checkpoint}', return_dict=True)

>>> question, text = "Who was Jim Henson?", "Jim Henson was a nice puppet"
>>> input_dict = tokenizer(question, text, return_tensors='tf')
Expand All @@ -688,7 +688,7 @@ def _prepare_output_docstrings(output_type, config_class):
>>> import tensorflow as tf

>>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}')
>>> model = {model_class}.from_pretrained('{checkpoint}', return_dict=True))
>>> model = {model_class}.from_pretrained('{checkpoint}', return_dict=True)

>>> inputs = tokenizer("Hello, my dog is cute", return_tensors="tf")
>>> inputs["labels"] = tf.reshape(tf.constant(1), (-1, 1)) # Batch size 1
Expand All @@ -705,7 +705,7 @@ def _prepare_output_docstrings(output_type, config_class):
>>> import tensorflow as tf

>>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}')
>>> model = {model_class}.from_pretrained('{checkpoint}', return_dict=True))
>>> model = {model_class}.from_pretrained('{checkpoint}', return_dict=True)

>>> inputs = tokenizer("The capital of France is {mask}.", return_tensors="tf")
>>> inputs["labels"] = tokenizer("The capital of France is Paris.", return_tensors="tf")["input_ids"]
Expand All @@ -722,7 +722,7 @@ def _prepare_output_docstrings(output_type, config_class):
>>> import tensorflow as tf

>>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}')
>>> model = {model_class}.from_pretrained('{checkpoint}', return_dict=True))
>>> model = {model_class}.from_pretrained('{checkpoint}', return_dict=True)

>>> inputs = tokenizer("Hello, my dog is cute", return_tensors="tf")
>>> outputs = model(inputs)
Expand All @@ -737,7 +737,7 @@ def _prepare_output_docstrings(output_type, config_class):
>>> import tensorflow as tf

>>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}')
>>> model = {model_class}.from_pretrained('{checkpoint}', return_dict=True))
>>> model = {model_class}.from_pretrained('{checkpoint}', return_dict=True)

>>> prompt = "In Italy, pizza served in formal settings, such as at a restaurant, is presented unsliced."
>>> choice0 = "It is eaten with a fork and a knife."
Expand All @@ -758,7 +758,7 @@ def _prepare_output_docstrings(output_type, config_class):
>>> import tensorflow as tf

>>> tokenizer = {tokenizer_class}.from_pretrained('{checkpoint}')
>>> model = {model_class}.from_pretrained('{checkpoint}', return_dict=True))
>>> model = {model_class}.from_pretrained('{checkpoint}', return_dict=True)

>>> inputs = tokenizer("Hello, my dog is cute", return_tensors="tf")
>>> outputs = model(inputs)
Expand Down