diff --git a/src/transformers/models/whisper/tokenization_whisper.py b/src/transformers/models/whisper/tokenization_whisper.py
index 5cfd2300346e..823a11c3ec99 100644
--- a/src/transformers/models/whisper/tokenization_whisper.py
+++ b/src/transformers/models/whisper/tokenization_whisper.py
@@ -673,13 +673,15 @@ def decode(
             token_ids (`Union[int, List[int], np.ndarray, torch.Tensor, tf.Tensor]`):
                 List of tokenized input ids. Can be obtained using the `__call__` method.
             skip_special_tokens (`bool`, *optional*, defaults to `False`):
-                Whether or not to remove special tokens in the decoding.
+                Whether or not to remove special tokens in the decoding. Will remove the previous tokens (pre-prompt)
+                if present.
             clean_up_tokenization_spaces (`bool`, *optional*):
                 Whether or not to clean up the tokenization spaces. If `None`, will default to
                 `self.clean_up_tokenization_spaces` (available in the `tokenizer_config`).
             output_offsets (`bool`, *optional*, defaults to `False`):
                 Whether or not to output the offsets of the tokens. This should only be set if the model predicted
-                timestamps.
+                timestamps. If there are previous tokens (pre-prompt) to decode, they will only appear in the decoded
+                text if they contain timestamp tokens.
             time_precision (`float`, *optional*, defaults to 0.02):
                 The time ratio to convert from token to time.
             decode_with_timestamps (`bool`, *optional*, defaults to `False`):
diff --git a/src/transformers/models/whisper/tokenization_whisper_fast.py b/src/transformers/models/whisper/tokenization_whisper_fast.py
index 6b6fb3a19900..11c2b4656711 100644
--- a/src/transformers/models/whisper/tokenization_whisper_fast.py
+++ b/src/transformers/models/whisper/tokenization_whisper_fast.py
@@ -319,13 +319,15 @@ def decode(
             token_ids (`Union[int, List[int], np.ndarray, torch.Tensor, tf.Tensor]`):
                 List of tokenized input ids. Can be obtained using the `__call__` method.
             skip_special_tokens (`bool`, *optional*, defaults to `False`):
-                Whether or not to remove special tokens in the decoding.
+                Whether or not to remove special tokens in the decoding. Will remove the previous tokens (pre-prompt)
+                if present.
             clean_up_tokenization_spaces (`bool`, *optional*):
                 Whether or not to clean up the tokenization spaces. If `None`, will default to
                 `self.clean_up_tokenization_spaces` (available in the `tokenizer_config`).
             output_offsets (`bool`, *optional*, defaults to `False`):
                 Whether or not to output the offsets of the tokens. This should only be set if the model predicted
-                timestamps.
+                timestamps. If there are previous tokens (pre-prompt) to decode, they will only appear in the decoded
+                text if they contain timestamp tokens.
             time_precision (`float`, *optional*, defaults to 0.02):
                 The time ratio to convert from token to time.
             decode_with_timestamps (`bool`, *optional*, defaults to `False`):