Fix quality and repo consistency
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@@ -68,7 +68,7 @@ Ready-made configurations include the following architectures:
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- M2M100
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- Marian
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- mBART
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- MobileBert
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- MobileBERT
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- OpenAI GPT-2
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- PLBart
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- RoBERTa
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@@ -1793,12 +1793,12 @@ if is_tf_available():
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"TFAutoModelForImageClassification",
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"TFAutoModelForMaskedLM",
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"TFAutoModelForMultipleChoice",
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"TFAutoModelForNextSentencePrediction",
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"TFAutoModelForPreTraining",
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"TFAutoModelForQuestionAnswering",
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"TFAutoModelForSeq2SeqLM",
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"TFAutoModelForSequenceClassification",
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"TFAutoModelForSpeechSeq2Seq",
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"TFAutoModelForNextSentencePrediction",
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"TFAutoModelForTableQuestionAnswering",
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"TFAutoModelForTokenClassification",
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"TFAutoModelForVision2Seq",
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@@ -103,12 +103,12 @@ if is_tf_available():
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"TFAutoModelForImageClassification",
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"TFAutoModelForMaskedLM",
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"TFAutoModelForMultipleChoice",
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"TFAutoModelForNextSentencePrediction",
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"TFAutoModelForPreTraining",
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"TFAutoModelForQuestionAnswering",
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"TFAutoModelForSeq2SeqLM",
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"TFAutoModelForSequenceClassification",
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"TFAutoModelForSpeechSeq2Seq",
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"TFAutoModelForNextSentencePrediction",
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"TFAutoModelForTableQuestionAnswering",
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"TFAutoModelForTokenClassification",
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"TFAutoModelForVision2Seq",
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@@ -335,6 +335,13 @@ class TFAutoModelForMultipleChoice(metaclass=DummyObject):
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requires_backends(self, ["tf"])
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class TFAutoModelForNextSentencePrediction(metaclass=DummyObject):
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_backends = ["tf"]
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def __init__(self, *args, **kwargs):
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requires_backends(self, ["tf"])
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class TFAutoModelForPreTraining(metaclass=DummyObject):
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_backends = ["tf"]
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