Add new dummy PT objects
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@ -1435,6 +1435,77 @@ class RobertaModel:
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requires_pytorch(self)
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SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST = None
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class SqueezeBertForMaskedLM:
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def __init__(self, *args, **kwargs):
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requires_pytorch(self)
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@classmethod
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def from_pretrained(self, *args, **kwargs):
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requires_pytorch(self)
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class SqueezeBertForMultipleChoice:
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def __init__(self, *args, **kwargs):
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requires_pytorch(self)
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@classmethod
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def from_pretrained(self, *args, **kwargs):
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requires_pytorch(self)
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class SqueezeBertForQuestionAnswering:
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def __init__(self, *args, **kwargs):
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requires_pytorch(self)
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@classmethod
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def from_pretrained(self, *args, **kwargs):
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requires_pytorch(self)
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class SqueezeBertForSequenceClassification:
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def __init__(self, *args, **kwargs):
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requires_pytorch(self)
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@classmethod
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def from_pretrained(self, *args, **kwargs):
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requires_pytorch(self)
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class SqueezeBertForTokenClassification:
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def __init__(self, *args, **kwargs):
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requires_pytorch(self)
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@classmethod
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def from_pretrained(self, *args, **kwargs):
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requires_pytorch(self)
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class SqueezeBertModel:
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def __init__(self, *args, **kwargs):
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requires_pytorch(self)
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@classmethod
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def from_pretrained(self, *args, **kwargs):
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requires_pytorch(self)
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class SqueezeBertModule:
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def __init__(self, *args, **kwargs):
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requires_pytorch(self)
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class SqueezeBertPreTrainedModel:
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def __init__(self, *args, **kwargs):
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requires_pytorch(self)
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@classmethod
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def from_pretrained(self, *args, **kwargs):
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requires_pytorch(self)
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T5_PRETRAINED_MODEL_ARCHIVE_LIST = None
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