Fix model templates (#9842)
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@@ -560,7 +560,7 @@ class TF{{cookiecutter.camelcase_modelname}}LMPredictionHead(tf.keras.layers.Lay
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def build(self, input_shape: tf.TensorShape):
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def build(self, input_shape: tf.TensorShape):
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self.bias = self.add_weight(shape=(self.vocab_size,), initializer="zeros", trainable=True, name="bias")
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self.bias = self.add_weight(shape=(self.vocab_size,), initializer="zeros", trainable=True, name="bias")
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super().build(input_shape=input_shape)
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super().build(input_shape)
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def get_output_embeddings(self) -> tf.keras.layers.Layer:
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def get_output_embeddings(self) -> tf.keras.layers.Layer:
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return self.input_embeddings
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return self.input_embeddings
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@@ -901,9 +901,7 @@ class TF{{cookiecutter.camelcase_modelname}}Model(TF{{cookiecutter.camelcase_mod
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hs = tf.convert_to_tensor(output.hidden_states) if self.config.output_hidden_states else None
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hs = tf.convert_to_tensor(output.hidden_states) if self.config.output_hidden_states else None
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attns = tf.convert_to_tensor(output.attentions) if self.config.output_attentions else None
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attns = tf.convert_to_tensor(output.attentions) if self.config.output_attentions else None
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return TFBaseModelOutput(
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return TFBaseModelOutput(last_hidden_state=output.last_hidden_state, hidden_states=hs, attentions=attns)
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last_hidden_state=output.last_hidden_state, hidden_states=hs, attentions=attns,
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)
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@add_start_docstrings("""{{cookiecutter.modelname}} Model with a `language modeling` head on top. """, {{cookiecutter.uppercase_modelname}}_START_DOCSTRING)
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@add_start_docstrings("""{{cookiecutter.modelname}} Model with a `language modeling` head on top. """, {{cookiecutter.uppercase_modelname}}_START_DOCSTRING)
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