diff --git a/src/transformers/models/instructblipvideo/modular_instructblipvideo.py b/src/transformers/models/instructblipvideo/modular_instructblipvideo.py
index f475a02626c0de..7184955af3aa56 100644
--- a/src/transformers/models/instructblipvideo/modular_instructblipvideo.py
+++ b/src/transformers/models/instructblipvideo/modular_instructblipvideo.py
@@ -261,7 +261,7 @@ def forward(
             output_hidden_states=output_hidden_states,
             return_dict=return_dict,
             interpolate_pos_encoding=interpolate_pos_encoding,
-        )git 
+        )
         image_embeds = vision_outputs[0]
 
         # step 2: forward the query tokens through the QFormer, using the image embeddings for cross-attention
diff --git a/src/transformers/utils/import_utils.py b/src/transformers/utils/import_utils.py
index ec1dbad698466b..32a647594741dd 100755
--- a/src/transformers/utils/import_utils.py
+++ b/src/transformers/utils/import_utils.py
@@ -1006,15 +1006,6 @@ def is_compressed_tensors_available():
     return _compressed_tensors_available
 
 
-def is_optimum_quanto_available():
-    # `importlib.metadata.version` doesn't work with `optimum.quanto`, need to put `optimum_quanto`
-    return _is_optimum_quanto_available
-
-
-def is_compressed_tensors_available():
-    return _compressed_tensors_available
-
-
 def is_auto_gptq_available():
     return _auto_gptq_available