Fixed model loader

app.py

@@ -2,7 +2,7 @@ import spaces
 import torch
 from diffusers import AutoencoderKLWan, WanImageToVideoPipeline, UniPCMultistepScheduler, WanTransformer3DModel, AutoModel, DiffusionPipeline
 from diffusers.utils import export_to_video
-from transformers import CLIPVisionModel, UMT5EncoderModel, CLIPTokenizer, CLIPTextModel, CLIPImageProcessor
+from transformers import CLIPVisionModel, UMT5EncoderModel, CLIPTextModel, CLIPImageProcessor
 from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
 import tempfile
 import re
@@ -32,8 +32,8 @@ try:
     # Load ALL components needed for the pipeline from the base model repo
     i2v_image_encoder = CLIPVisionModel.from_pretrained(I2V_BASE_MODEL_ID, subfolder="image_encoder", torch_dtype=torch.float32)
     i2v_vae = AutoencoderKLWan.from_pretrained(I2V_BASE_MODEL_ID, subfolder="vae", torch_dtype=torch.float32)
-    i2v_text_encoder = CLIPTextModel.from_pretrained(I2V_BASE_MODEL_ID, subfolder="text_encoder", torch_dtype=torch.bfloat16)
-    i2v_tokenizer = CLIPTokenizer.from_pretrained(I2V_BASE_MODEL_ID, subfolder="tokenizer")
+    i2v_text_encoder = UMT5EncoderModel.from_pretrained(I2V_BASE_MODEL_ID, subfolder="text_encoder", torch_dtype=torch.bfloat16)
+    i2v_tokenizer = AutoTokenizer.from_pretrained(I2V_BASE_MODEL_ID, subfolder="tokenizer")
     i2v_image_processor = CLIPImageProcessor.from_pretrained(I2V_BASE_MODEL_ID, subfolder="image_processor")
     
     # Create scheduler with custom flow_shift
@@ -43,7 +43,8 @@ try:
     
     # Load the main transformer from the repo and filename
     i2v_transformer = WanTransformer3DModel.from_single_file(
-        "https://huggingface.co/vrgamedevgirl84/Wan14BT2VFusioniX/blob/main/Wan14Bi2vFusioniX.safetensors",
+        I2V_FUSIONX_REPO_ID,
+        filename=I2V_FUSIONX_FILENAME,
         torch_dtype=torch.bfloat16
     )