diff --git a/src/diffusers/loaders/single_file.py b/src/diffusers/loaders/single_file.py
index f8ef9a8a74ab..c0cbfc713857 100644
--- a/src/diffusers/loaders/single_file.py
+++ b/src/diffusers/loaders/single_file.py
@@ -23,6 +23,7 @@
 from ..utils import deprecate, is_transformers_available, logging
 from .single_file_utils import (
     SingleFileComponentError,
+    _is_legacy_scheduler_kwargs,
     _is_model_weights_in_cached_folder,
     _legacy_load_clip_tokenizer,
     _legacy_load_safety_checker,
@@ -42,7 +43,6 @@
 # Legacy behaviour. `from_single_file` does not load the safety checker unless explicitly provided
 SINGLE_FILE_OPTIONAL_COMPONENTS = ["safety_checker"]
 
-
 if is_transformers_available():
     import transformers
     from transformers import PreTrainedModel, PreTrainedTokenizer
@@ -135,7 +135,7 @@ def load_single_file_sub_model(
             class_obj, checkpoint=checkpoint, config=cached_model_config_path, local_files_only=local_files_only
         )
 
-    elif is_diffusers_scheduler and is_legacy_loading:
+    elif is_diffusers_scheduler and (is_legacy_loading or _is_legacy_scheduler_kwargs(kwargs)):
         loaded_sub_model = _legacy_load_scheduler(
             class_obj, checkpoint=checkpoint, component_name=name, original_config=original_config, **kwargs
         )
diff --git a/src/diffusers/loaders/single_file_utils.py b/src/diffusers/loaders/single_file_utils.py
index 9c2a2cbf2942..d099f722187a 100644
--- a/src/diffusers/loaders/single_file_utils.py
+++ b/src/diffusers/loaders/single_file_utils.py
@@ -269,6 +269,7 @@
 ]
 OPEN_CLIP_PREFIX = "conditioner.embedders.0.model."
 LDM_OPEN_CLIP_TEXT_PROJECTION_DIM = 1024
+SCHEDULER_LEGACY_KWARGS = ["prediction_type", "scheduler_type"]
 
 VALID_URL_PREFIXES = ["https://huggingface.co/", "huggingface.co/", "hf.co/", "https://hf.co/"]
 
@@ -318,6 +319,10 @@ def _is_model_weights_in_cached_folder(cached_folder, name):
     return weights_exist
 
 
+def _is_legacy_scheduler_kwargs(kwargs):
+    return any(k in SCHEDULER_LEGACY_KWARGS for k in kwargs.keys())
+
+
 def load_single_file_checkpoint(
     pretrained_model_link_or_path,
     force_download=False,
@@ -1477,14 +1482,22 @@ def _legacy_load_scheduler(
 
     if scheduler_type is not None:
         deprecation_message = (
-            "Please pass an instance of a Scheduler object directly to the `scheduler` argument in `from_single_file`."
+            "Please pass an instance of a Scheduler object directly to the `scheduler` argument in `from_single_file`\n\n"
+            "Example:\n\n"
+            "from diffusers import StableDiffusionPipeline, DDIMScheduler\n\n"
+            "scheduler = DDIMScheduler()\n"
+            "pipe = StableDiffusionPipeline.from_single_file(<checkpoint path>, scheduler=scheduler)\n"
         )
         deprecate("scheduler_type", "1.0.0", deprecation_message)
 
     if prediction_type is not None:
         deprecation_message = (
-            "Please configure an instance of a Scheduler with the appropriate `prediction_type` "
-            "and pass the object directly to the `scheduler` argument in `from_single_file`."
+            "Please configure an instance of a Scheduler with the appropriate `prediction_type` and "
+            "pass the object directly to the `scheduler` argument in `from_single_file`.\n\n"
+            "Example:\n\n"
+            "from diffusers import StableDiffusionPipeline, DDIMScheduler\n\n"
+            'scheduler = DDIMScheduler(prediction_type="v_prediction")\n'
+            "pipe = StableDiffusionPipeline.from_single_file(<checkpoint path>, scheduler=scheduler)\n"
         )
         deprecate("prediction_type", "1.0.0", deprecation_message)