Update app.py

app.py

@@ -13,13 +13,8 @@ from diffusers.utils import export_to_video
 import random
 from transformers import pipeline
 
-# Hugging Face 토큰 가져오기
-hf_token = os.getenv("HF_TOKEN")
-if not hf_token:
-    raise ValueError("HF_TOKEN environment variable is not set. Please set it to your Hugging Face token.")
-
-# 번역 모델 로드 (토큰 인증 추가)
-translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en", use_auth_token=hf_token)
+# 번역 모델 로드
+translator = pipeline("translation", model="Helsinki-NLP/opus-mt-ko-en")
 
 # 한글 메뉴 이름 dictionary
 korean_labels = {
@@ -41,21 +36,15 @@ korean_labels = {
     "Seed": "시드"
 }
 
-# load pipelines (토큰 인증 추가)
-# base_model = "black-forest-labs/FLUX.1-dev"
-
+# load pipelines
 base_model = "black-forest-labs/FLUX.1-schnell"
 
-
-taef1 = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=torch.bfloat16, use_auth_token=hf_token).to("cuda")
+taef1 = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=torch.bfloat16).to("cuda")
 pipe = FluxPipeline.from_pretrained(base_model,
                                     vae=taef1,
-                                    torch_dtype=torch.bfloat16,
-                                    use_auth_token=hf_token)
+                                    torch_dtype=torch.bfloat16)
 
 pipe.transformer.to(memory_format=torch.channels_last)
-#pipe.transformer = torch.compile(pipe.transformer, mode="max-autotune", fullgraph=True)
-# pipe.enable_model_cpu_offload()
 clip_slider = CLIPSliderFlux(pipe, device=torch.device("cuda"))
 
 MAX_SEED = 2**32-1
@@ -85,7 +74,7 @@ def convert_to_centered_scale(num):
 
 def translate_if_korean(text):
     if any('\u3131' <= char <= '\u3163' or '\uac00' <= char <= '\ud7a3' for char in text):
-        return translator(text, use_auth_token=hf_token)[0]['translation_text']
+        return translator(text)[0]['translation_text']
     return text
 
 @spaces.GPU(duration=85)