Update optimum/exporters/openvino/model_patcher.py

optimum/exporters/openvino/model_patcher.py

@@ -2516,7 +2516,7 @@ def _falcon_prepare_4d_causal_attention_mask_with_cache_position(
         # In this case we assume that the mask comes already in inverted form and requires no inversion or slicing.
         causal_mask = attention_mask
     else:
-        # different from original allow to provide min_dtype as parameter
+        # different from original: allow to provide min_dtype as parameter
         min_dtype = torch.finfo(dtype).min if "min_dtype" not in kwargs else kwargs["min_dtype"]
         causal_mask = torch.full((sequence_length, target_length), fill_value=min_dtype, dtype=dtype, device=device)
         if sequence_length != 1: