fix condition where torch_dtype auto collides with model_kwargs.

src/transformers/pipelines/__init__.py

@@ -1005,13 +1005,21 @@ def pipeline(
         model_kwargs["device_map"] = device_map
     if torch_dtype is not None:
         if "torch_dtype" in model_kwargs:
-            raise ValueError(
-                'You cannot use both `pipeline(... torch_dtype=..., model_kwargs={"torch_dtype":...})` as those'
-                " arguments might conflict, use only one.)"
-            )
-        if isinstance(torch_dtype, str) and hasattr(torch, torch_dtype):
-            torch_dtype = getattr(torch, torch_dtype)
-        model_kwargs["torch_dtype"] = torch_dtype
+            # If the user did not explicitly provide `torch_dtype` (i.e. the function default "auto" is still
+            # present) but a value is supplied inside `model_kwargs`, we silently defer to the latter instead of
+            # raising. This prevents false positives like providing `torch_dtype` only via `model_kwargs` while the
+            # top-level argument keeps its default value "auto".
+            if torch_dtype == "auto":
+                torch_dtype = None
+            else:
+                raise ValueError(
+                    'You cannot use both `pipeline(... torch_dtype=..., model_kwargs={"torch_dtype":...})` as those'
+                    " arguments might conflict, use only one.)"
+                )
+        if torch_dtype is not None:
+            if isinstance(torch_dtype, str) and hasattr(torch, torch_dtype):
+                torch_dtype = getattr(torch, torch_dtype)
+            model_kwargs["torch_dtype"] = torch_dtype
 
     model_name = model if isinstance(model, str) else None