Update app.py

app.py

@@ -67,13 +67,28 @@ tokenizer_3 = AutoTokenizer.from_pretrained(
 
 # Ensure model and scheduler are initialized in GPU-enabled function
 if torch.cuda.is_available():
-    pipe = StableDiffusion3Pipeline.from_pretrained(repo, vae=vae, transformer=transformer, tokenizer_3=tokenizer_3, text_encoder_3=text_encoder_3, torch_dtype=torch.float16).to("cuda")
-    pipe2 = StableDiffusion3Img2ImgPipeline.from_pretrained(repo, vae=vae, transformer=transformer, tokenizer_3=tokenizer_3, text_encoder_3=text_encoder_3, torch_dtype=torch.float16).to("cuda")
+    pipe = StableDiffusion3Pipeline.from_pretrained(
+        repo, 
+        vae=vae, 
+        transformer=transformer, 
+        tokenizer_3=tokenizer_3, 
+        text_encoder_3=text_encoder_3, 
+        torch_dtype=torch.float16).to("cuda")
+    pipe2 = StableDiffusion3Img2ImgPipeline.from_pretrained(
+        repo, 
+        vae=vae, 
+        transformer=transformer, 
+        tokenizer_3=tokenizer_3, 
+        text_encoder_3=text_encoder_3, 
+        torch_dtype=torch.float16).to("cuda")
 
 pipe.scheduler = FlowMatchEulerDiscreteScheduler.from_config(pipe.scheduler.config)
 pipe2.scheduler = FlowMatchEulerDiscreteScheduler.from_config(pipe2.scheduler.config)
 
-print(pipe.tokenizer_max_length)
+print(pipe.tokenizer.model_max_length)
+print(pipe.tokenizer_3.model_max_length)
+
+pipe.tokenizer_max_length=512
 
 # Function 
 @spaces.GPU()