diff --git a/src/transformers/generation_utils.py b/src/transformers/generation_utils.py
index 8f6dc6a383a7..637b723c88de 100644
--- a/src/transformers/generation_utils.py
+++ b/src/transformers/generation_utils.py
@@ -1200,7 +1200,7 @@ def generate(
         input_ids_seq_length = input_ids.shape[-1]
         if max_length is None and max_new_tokens is None:
             warnings.warn(
-                "Neither `max_length` nor `max_new_tokens` have been set, `max_length` will default to "
+                "Neither `max_length` nor `max_new_tokens` has been set, `max_length` will default to "
                 f"{self.config.max_length} (`self.config.max_length`). Controlling `max_length` via the config is "
                 "deprecated and `max_length` will be removed from the config in v5 of Transformers -- we recommend "
                 "using `max_new_tokens` to control the maximum length of the generation.",
diff --git a/src/transformers/models/fsmt/modeling_fsmt.py b/src/transformers/models/fsmt/modeling_fsmt.py
index d44bc80363d0..f469266d7454 100644
--- a/src/transformers/models/fsmt/modeling_fsmt.py
+++ b/src/transformers/models/fsmt/modeling_fsmt.py
@@ -220,7 +220,7 @@
         input_ids (`torch.LongTensor` of shape `(batch_size, sequence_length)`):
             Indices of input sequence tokens in the vocabulary.
 
-            IIndices can be obtained using [`FSTMTokenizer`]. See [`PreTrainedTokenizer.encode`] and
+            Indices can be obtained using [`FSTMTokenizer`]. See [`PreTrainedTokenizer.encode`] and
             [`PreTrainedTokenizer.__call__`] for details.
 
             [What are input IDs?](../glossary#input-ids)