small clean-up

app.py

@@ -45,11 +45,11 @@ class Args:
         self.device = 'cuda:0'
         self.num_nodes = 1
         self.dtype = 'bf16'
-        self.exp_path = str(Path(os.environ.get('MODELS_DIR', 'pretrained_models')) / "OmniAvatar-1.3B")
-        self.dit_path = str(Path(os.environ.get('MODELS_DIR', 'pretrained_models')) / "Wan2.1-T2V-1.3B/diffusion_pytorch_model.safetensors")
-        self.text_encoder_path = str(Path(os.environ.get('MODELS_DIR', 'pretrained_models')) / "Wan2.1-T2V-1.3B/models_t5_umt5-xxl-enc-bf16.pth")
-        self.vae_path = str(Path(os.environ.get('MODELS_DIR', 'pretrained_models')) / "Wan2.1-T2V-1.3B/Wan2.1_VAE.pth")
-        self.wav2vec_path = str(Path(os.environ.get('MODELS_DIR', 'pretrained_models')) / "wav2vec2-base-960h")
+        self.exp_path = str(MODELS_DIR / "OmniAvatar-1.3B")
+        self.dit_path = str(MODELS_DIR / "Wan2.1-T2V-1.3B/diffusion_pytorch_model.safetensors")
+        self.text_encoder_path = str(MODELS_DIR / "Wan2.1-T2V-1.3B/models_t5_umt5-xxl-enc-bf16.pth")
+        self.vae_path = str(MODELS_DIR / "Wan2.1-T2V-1.3B/Wan2.1_VAE.pth")
+        self.wav2vec_path = str(MODELS_DIR / "wav2vec2-base-960h")
         self.train_architecture = 'lora'
         self.lora_rank = 128
         self.lora_alpha = 64.0