diff --git a/finetrainers/cogvideox/cogvideox_lora.py b/finetrainers/cogvideox/cogvideox_lora.py
index c3b754a..9d3a77c 100644
--- a/finetrainers/cogvideox/cogvideox_lora.py
+++ b/finetrainers/cogvideox/cogvideox_lora.py
@@ -42,8 +42,9 @@ def load_diffusion_models(
     cache_dir: Optional[str] = None,
     **kwargs,
 ):
+    subfolder = kwargs.get("subfolder", None)
     transformer = CogVideoXTransformer3DModel.from_pretrained(
-        model_id, subfolder="transformer", torch_dtype=transformer_dtype, revision=revision, cache_dir=cache_dir
+        model_id, subfolder=subfolder, torch_dtype=transformer_dtype, revision=revision, cache_dir=cache_dir
     )
     scheduler = CogVideoXDDIMScheduler.from_pretrained(model_id, subfolder="scheduler")
     return {"transformer": transformer, "scheduler": scheduler}
diff --git a/finetrainers/hunyuan_video/hunyuan_video_lora.py b/finetrainers/hunyuan_video/hunyuan_video_lora.py
index 9bfea53..450101d 100644
--- a/finetrainers/hunyuan_video/hunyuan_video_lora.py
+++ b/finetrainers/hunyuan_video/hunyuan_video_lora.py
@@ -63,8 +63,9 @@ def load_diffusion_models(
     cache_dir: Optional[str] = None,
     **kwargs,
 ) -> Dict[str, Union[nn.Module, FlowMatchEulerDiscreteScheduler]]:
+    subfolder = kwargs.get("subfolder", None)
     transformer = HunyuanVideoTransformer3DModel.from_pretrained(
-        model_id, subfolder="transformer", torch_dtype=transformer_dtype, revision=revision, cache_dir=cache_dir
+        model_id, subfolder=subfolder, torch_dtype=transformer_dtype, revision=revision, cache_dir=cache_dir
     )
     scheduler = FlowMatchEulerDiscreteScheduler(shift=shift)
     return {"transformer": transformer, "scheduler": scheduler}
diff --git a/finetrainers/ltx_video/ltx_video_lora.py b/finetrainers/ltx_video/ltx_video_lora.py
index 0e1af9b..7a80543 100644
--- a/finetrainers/ltx_video/ltx_video_lora.py
+++ b/finetrainers/ltx_video/ltx_video_lora.py
@@ -45,8 +45,9 @@ def load_diffusion_models(
     cache_dir: Optional[str] = None,
     **kwargs,
 ) -> Dict[str, nn.Module]:
+    subfolder = kwargs.get("subfolder", None)
     transformer = LTXVideoTransformer3DModel.from_pretrained(
-        model_id, subfolder="transformer", torch_dtype=transformer_dtype, revision=revision, cache_dir=cache_dir
+        model_id, subfolder=subfolder, torch_dtype=transformer_dtype, revision=revision, cache_dir=cache_dir
     )
     scheduler = FlowMatchEulerDiscreteScheduler()
     return {"transformer": transformer, "scheduler": scheduler}