Update app.py

app.py

@@ -20,7 +20,10 @@ device = 'cuda' if torch.cuda.is_available() else 'cpu'
 model_path = "MeissonFlow/Meissonic"
 model = Transformer2DModel.from_pretrained(model_path, subfolder="transformer")
 vq_model = VQModel.from_pretrained(model_path, subfolder="vqvae")
-text_encoder = CLIPTextModelWithProjection.from_pretrained(model_path, subfolder="text_encoder")
+# text_encoder = CLIPTextModelWithProjection.from_pretrained(model_path, subfolder="text_encoder")
+text_encoder = CLIPTextModelWithProjection.from_pretrained(  #more stable sampling for some cases
+            "laion/CLIP-ViT-H-14-laion2B-s32B-b79K"
+        )
 tokenizer = CLIPTokenizer.from_pretrained(model_path, subfolder="tokenizer")
 scheduler = Scheduler.from_pretrained(model_path, subfolder="scheduler")
 pipe = Pipeline(vq_model, tokenizer=tokenizer, text_encoder=text_encoder, transformer=model, scheduler=scheduler)