fix: using a slow image processor as `use_fast` is unset and a slow processor was saved with this model

app.py

@@ -43,8 +43,8 @@ else:
 # 从 HF 加载预训练模型
 class LRMGeneratorWrapper:
     def __init__(self):
-        self.config = AutoConfig.from_pretrained("yanranxiaoxi/image-upscale", trust_remote_code=True, token=os.environ.get('MODEL_ACCESS_TOKEN'))
-        self.model = AutoModel.from_pretrained("yanranxiaoxi/image-upscale", trust_remote_code=True, token=os.environ.get('MODEL_ACCESS_TOKEN'))
+        self.config = AutoConfig.from_pretrained("yanranxiaoxi/image-upscale", trust_remote_code=True, token=os.environ.get('MODEL_ACCESS_TOKEN'), use_fast=False)
+        self.model = AutoModel.from_pretrained("yanranxiaoxi/image-upscale", trust_remote_code=True, token=os.environ.get('MODEL_ACCESS_TOKEN'), use_fast=False)
         self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
         self.model.to(self.device)
         self.model.eval()