Update video_service.py

video_service.py

@@ -261,12 +261,10 @@ class VideoService:
             return yaml.safe_load(file)
 
     def _load_models(self):
-        models_dir = "downloaded_models_gradio"
-        Path(models_dir).mkdir(parents=True, exist_ok=True)
         LTX_REPO = "Lightricks/LTX-Video"
-        distilled_model_path = hf_hub_download(repo_id=LTX_REPO, filename=self.config["checkpoint_path"], local_dir=models_dir, cache_dir=os.getenv("HF_HOME_CACHE"), token=os.getenv("HF_TOKEN"))
+        distilled_model_path = hf_hub_download(repo_id=LTX_REPO, filename=self.config["checkpoint_path"], local_dir=os.getenv("HF_HOME"), cache_dir=os.getenv("HF_HOME_CACHE"), token=os.getenv("HF_TOKEN"))
         self.config["checkpoint_path"] = distilled_model_path
-        spatial_upscaler_path = hf_hub_download(repo_id=LTX_REPO, filename=self.config["spatial_upscaler_model_path"], local_dir=models_dir, cache_dir=os.getenv("HF_HOME_CACHE"), token=os.getenv("HF_TOKEN"))
+        spatial_upscaler_path = hf_hub_download(repo_id=LTX_REPO, filename=self.config["spatial_upscaler_model_path"], local_dir=os.getenv("HF_HOME"), cache_dir=os.getenv("HF_HOME_CACHE"), token=os.getenv("HF_TOKEN"))
         self.config["spatial_upscaler_model_path"] = spatial_upscaler_path
         pipeline = create_ltx_video_pipeline(ckpt_path=self.config["checkpoint_path"], precision=self.config["precision"], text_encoder_model_name_or_path=self.config["text_encoder_model_name_or_path"], sampler=self.config["sampler"], device="cpu", enhance_prompt=False, prompt_enhancer_image_caption_model_name_or_path=self.config["prompt_enhancer_image_caption_model_name_or_path"], prompt_enhancer_llm_model_name_or_path=self.config["prompt_enhancer_llm_model_name_or_path"])
         latent_upsampler = None