diff --git a/src/transformers/modeling_tf_utils.py b/src/transformers/modeling_tf_utils.py
index be4180f12dca3a..e27b09872c7c1e 100644
--- a/src/transformers/modeling_tf_utils.py
+++ b/src/transformers/modeling_tf_utils.py
@@ -1237,7 +1237,13 @@ def input_signature(self) -> Dict[str, tf.TensorSpec]:
                 text_dims = 3
             else:
                 text_dims = 2
-            for input_name in ("input_ids", "attention_mask", "token_type_ids", "decoder_input_ids"):
+            for input_name in (
+                "input_ids",
+                "attention_mask",
+                "token_type_ids",
+                "decoder_input_ids",
+                "decoder_attention_mask",
+            ):
                 if input_name in model_inputs:
                     sig[input_name] = tf.TensorSpec([None] * text_dims, tf.int32, name=input_name)
         if "pixel_values" in model_inputs:
diff --git a/src/transformers/models/bart/modeling_tf_bart.py b/src/transformers/models/bart/modeling_tf_bart.py
index a823544a3d6c80..32608ab896b545 100644
--- a/src/transformers/models/bart/modeling_tf_bart.py
+++ b/src/transformers/models/bart/modeling_tf_bart.py
@@ -482,15 +482,6 @@ class TFBartPretrainedModel(TFPreTrainedModel):
     config_class = BartConfig
     base_model_prefix = "model"
 
-    @property
-    def input_signature(self):
-        return {
-            "input_ids": tf.TensorSpec((None, None), tf.int32, name="input_ids"),
-            "attention_mask": tf.TensorSpec((None, None), tf.int32, name="attention_mask"),
-            "decoder_input_ids": tf.TensorSpec((None, None), tf.int32, name="decoder_input_ids"),
-            "decoder_attention_mask": tf.TensorSpec((None, None), tf.int32, name="decoder_attention_mask"),
-        }
-
     @property
     def dummy_inputs(self):
         dummy_inputs = super().dummy_inputs
diff --git a/src/transformers/models/blenderbot/modeling_tf_blenderbot.py b/src/transformers/models/blenderbot/modeling_tf_blenderbot.py
index 5ef68f081eed27..6121e24a120950 100644
--- a/src/transformers/models/blenderbot/modeling_tf_blenderbot.py
+++ b/src/transformers/models/blenderbot/modeling_tf_blenderbot.py
@@ -461,15 +461,6 @@ class TFBlenderbotPreTrainedModel(TFPreTrainedModel):
     config_class = BlenderbotConfig
     base_model_prefix = "model"
 
-    @property
-    def input_signature(self):
-        return {
-            "input_ids": tf.TensorSpec((None, None), tf.int32, name="input_ids"),
-            "attention_mask": tf.TensorSpec((None, None), tf.int32, name="attention_mask"),
-            "decoder_input_ids": tf.TensorSpec((None, None), tf.int32, name="decoder_input_ids"),
-            "decoder_attention_mask": tf.TensorSpec((None, None), tf.int32, name="decoder_attention_mask"),
-        }
-
 
 BLENDERBOT_START_DOCSTRING = r"""
     This model inherits from [`TFPreTrainedModel`]. Check the superclass documentation for the generic methods the
diff --git a/src/transformers/models/blenderbot_small/modeling_tf_blenderbot_small.py b/src/transformers/models/blenderbot_small/modeling_tf_blenderbot_small.py
index d27536aa40db22..e56926c16a43aa 100644
--- a/src/transformers/models/blenderbot_small/modeling_tf_blenderbot_small.py
+++ b/src/transformers/models/blenderbot_small/modeling_tf_blenderbot_small.py
@@ -461,15 +461,6 @@ class TFBlenderbotSmallPreTrainedModel(TFPreTrainedModel):
     config_class = BlenderbotSmallConfig
     base_model_prefix = "model"
 
-    @property
-    def input_signature(self):
-        return {
-            "input_ids": tf.TensorSpec((None, None), tf.int32, name="input_ids"),
-            "attention_mask": tf.TensorSpec((None, None), tf.int32, name="attention_mask"),
-            "decoder_input_ids": tf.TensorSpec((None, None), tf.int32, name="decoder_input_ids"),
-            "decoder_attention_mask": tf.TensorSpec((None, None), tf.int32, name="decoder_attention_mask"),
-        }
-
 
 BLENDERBOT_SMALL_START_DOCSTRING = r"""
     This model inherits from [`TFPreTrainedModel`]. Check the superclass documentation for the generic methods the
diff --git a/src/transformers/models/blip/modeling_tf_blip.py b/src/transformers/models/blip/modeling_tf_blip.py
index 2e04a4db91c714..18c4d05714b2ba 100644
--- a/src/transformers/models/blip/modeling_tf_blip.py
+++ b/src/transformers/models/blip/modeling_tf_blip.py
@@ -1206,12 +1206,6 @@ def _shift_right(self, input_ids):
 
         return shifted_input_ids
 
-    @property
-    def input_signature(self):
-        base_sig = super().input_signature
-        base_sig["decoder_input_ids"] = base_sig["input_ids"]
-        return base_sig
-
     @unpack_inputs
     @add_start_docstrings_to_model_forward(BLIP_VISION_INPUTS_DOCSTRING)
     @replace_return_docstrings(output_type=TFBlipTextVisionModelOutput, config_class=BlipVisionConfig)
diff --git a/src/transformers/models/encoder_decoder/modeling_tf_encoder_decoder.py b/src/transformers/models/encoder_decoder/modeling_tf_encoder_decoder.py
index 4112a0fc74f56a..bc135d44d8c209 100644
--- a/src/transformers/models/encoder_decoder/modeling_tf_encoder_decoder.py
+++ b/src/transformers/models/encoder_decoder/modeling_tf_encoder_decoder.py
@@ -272,13 +272,6 @@ def __init__(
                 "following discussion on GitHub: https://github.com/huggingface/transformers/issues/23350"
             )
 
-    @property
-    def input_signature(self):
-        return {
-            "input_ids": tf.TensorSpec([None, None], dtype=tf.int32),
-            "decoder_input_ids": tf.TensorSpec([None, None], dtype=tf.int32),
-        }
-
     def get_encoder(self):
         return self.encoder
 
diff --git a/src/transformers/models/marian/modeling_tf_marian.py b/src/transformers/models/marian/modeling_tf_marian.py
index e9179ef3f8081f..3ccc2528fe7629 100644
--- a/src/transformers/models/marian/modeling_tf_marian.py
+++ b/src/transformers/models/marian/modeling_tf_marian.py
@@ -498,15 +498,6 @@ class TFMarianPreTrainedModel(TFPreTrainedModel):
     config_class = MarianConfig
     base_model_prefix = "model"
 
-    @property
-    def input_signature(self):
-        return {
-            "input_ids": tf.TensorSpec((None, None), tf.int32, name="input_ids"),
-            "attention_mask": tf.TensorSpec((None, None), tf.int32, name="attention_mask"),
-            "decoder_input_ids": tf.TensorSpec((None, None), tf.int32, name="decoder_input_ids"),
-            "decoder_attention_mask": tf.TensorSpec((None, None), tf.int32, name="decoder_attention_mask"),
-        }
-
 
 MARIAN_START_DOCSTRING = r"""
     This model inherits from [`TFPreTrainedModel`]. Check the superclass documentation for the generic methods the
diff --git a/src/transformers/models/mbart/modeling_tf_mbart.py b/src/transformers/models/mbart/modeling_tf_mbart.py
index 68b5a697e571e3..394df341b45dd5 100644
--- a/src/transformers/models/mbart/modeling_tf_mbart.py
+++ b/src/transformers/models/mbart/modeling_tf_mbart.py
@@ -465,15 +465,6 @@ class TFMBartPreTrainedModel(TFPreTrainedModel):
     config_class = MBartConfig
     base_model_prefix = "model"
 
-    @property
-    def input_signature(self):
-        return {
-            "input_ids": tf.TensorSpec((None, None), tf.int32, name="input_ids"),
-            "attention_mask": tf.TensorSpec((None, None), tf.int32, name="attention_mask"),
-            "decoder_input_ids": tf.TensorSpec((None, None), tf.int32, name="decoder_input_ids"),
-            "decoder_attention_mask": tf.TensorSpec((None, None), tf.int32, name="decoder_attention_mask"),
-        }
-
 
 MBART_START_DOCSTRING = r"""
     This model inherits from [`TFPreTrainedModel`]. Check the superclass documentation for the generic methods the
diff --git a/src/transformers/models/pegasus/modeling_tf_pegasus.py b/src/transformers/models/pegasus/modeling_tf_pegasus.py
index d3e9e6982d7d80..547beb99b03a0a 100644
--- a/src/transformers/models/pegasus/modeling_tf_pegasus.py
+++ b/src/transformers/models/pegasus/modeling_tf_pegasus.py
@@ -500,15 +500,6 @@ class TFPegasusPreTrainedModel(TFPreTrainedModel):
     config_class = PegasusConfig
     base_model_prefix = "model"
 
-    @property
-    def input_signature(self):
-        return {
-            "input_ids": tf.TensorSpec((None, None), tf.int32, name="input_ids"),
-            "attention_mask": tf.TensorSpec((None, None), tf.int32, name="attention_mask"),
-            "decoder_input_ids": tf.TensorSpec((None, None), tf.int32, name="decoder_input_ids"),
-            "decoder_attention_mask": tf.TensorSpec((None, None), tf.int32, name="decoder_attention_mask"),
-        }
-
 
 PEGASUS_START_DOCSTRING = r"""
     This model inherits from [`TFPreTrainedModel`]. Check the superclass documentation for the generic methods the
diff --git a/src/transformers/models/t5/modeling_tf_t5.py b/src/transformers/models/t5/modeling_tf_t5.py
index 7babad30897515..57a3fa60f8d452 100644
--- a/src/transformers/models/t5/modeling_tf_t5.py
+++ b/src/transformers/models/t5/modeling_tf_t5.py
@@ -862,15 +862,6 @@ class TFT5PreTrainedModel(TFPreTrainedModel):
     # names with a '.' represents the authorized unexpected/missing layers when a TF model is loaded from a PT model
     _keys_to_ignore_on_load_unexpected = [r"decoder\Wblock[\W_0]+layer[\W_1]+EncDecAttention\Wrelative_attention_bias"]
 
-    @property
-    def input_signature(self):
-        return {
-            "input_ids": tf.TensorSpec((None, None), tf.int32, name="input_ids"),
-            "attention_mask": tf.TensorSpec((None, None), tf.int32, name="attention_mask"),
-            "decoder_input_ids": tf.TensorSpec((None, None), tf.int32, name="decoder_input_ids"),
-            "decoder_attention_mask": tf.TensorSpec((None, None), tf.int32, name="decoder_attention_mask"),
-        }
-
     def get_input_embeddings(self):
         return self.shared
 
diff --git a/src/transformers/models/xglm/modeling_tf_xglm.py b/src/transformers/models/xglm/modeling_tf_xglm.py
index d0085fd8cc26f8..b06e071d310590 100644
--- a/src/transformers/models/xglm/modeling_tf_xglm.py
+++ b/src/transformers/models/xglm/modeling_tf_xglm.py
@@ -617,15 +617,6 @@ class TFXGLMPreTrainedModel(TFPreTrainedModel):
     config_class = XGLMConfig
     base_model_prefix = "model"
 
-    @property
-    def input_signature(self):
-        return {
-            "input_ids": tf.TensorSpec((None, None), tf.int32, name="input_ids"),
-            "attention_mask": tf.TensorSpec((None, None), tf.int32, name="attention_mask"),
-            "decoder_input_ids": tf.TensorSpec((None, None), tf.int32, name="decoder_input_ids"),
-            "decoder_attention_mask": tf.TensorSpec((None, None), tf.int32, name="decoder_attention_mask"),
-        }
-
 
 XGLM_START_DOCSTRING = r"""
     This model inherits from [`TFPreTrainedModel`]. Check the superclass documentation for the generic methods the