Update app.py

app.py

@@ -42,42 +42,38 @@ JS = """function () {
 }"""
 
 
-vae = AutoencoderKL.from_pretrained(
-    repo,
-    subfolder="vae",
-    torch_dtype=torch.float16,
-)
+# vae = AutoencoderKL.from_pretrained(
+#     repo,
+#     subfolder="vae",
+#     torch_dtype=torch.float16,
+# )
 
-transformer = SD3Transformer2DModel.from_pretrained(
-    repo, 
-    subfolder="transformer",
-    torch_dtype=torch.float16,
-)
+# transformer = SD3Transformer2DModel.from_pretrained(
+#     repo, 
+#     subfolder="transformer",
+#     torch_dtype=torch.float16,
+# )
 
 
-text_encoder_3 = T5EncoderModel.from_pretrained(
-    repo, 
-    subfolder="text_encoder_3", 
-)
+# text_encoder_3 = T5EncoderModel.from_pretrained(
+#     repo, 
+#     subfolder="text_encoder_3", 
+# )
 
-tokenizer_3 = AutoTokenizer.from_pretrained(
-    repo, 
-    subfolder="tokenizer_3",
-    torch_dtype=torch.float16,
-)
+# tokenizer_3 = AutoTokenizer.from_pretrained(
+#     repo, 
+#     subfolder="tokenizer_3",
+#     torch_dtype=torch.float16,
+# )
 
 
 # Ensure model and scheduler are initialized in GPU-enabled function
 if torch.cuda.is_available():
     pipe = StableDiffusion3Pipeline.from_pretrained(
         repo,
-        vae=vae,
-        transformer=transformer,
         torch_dtype=torch.float16).to("cuda")
     pipe2 = StableDiffusion3Img2ImgPipeline.from_pretrained(
         repo,
-        vae=vae,
-        transformer=transformer,
         torch_dtype=torch.float16).to("cuda")