Update app.py

app.py

@@ -51,14 +51,11 @@ with open('loras.json', 'r') as f:
 #torch.cuda.empty_cache()
 #pipe = diffusers.ZImagePipeline.from_pretrained("dimitribarbot/Z-Image-Turbo-BF16", torch_dtype=torch.bfloat16)
 #pipe = diffusers.ZImagePipeline.from_pretrained("AlekseyCalvin/Z_Image_Deturbo_Diffusers", torch_dtype=torch.bfloat16)
-vae = AutoencoderKL.from_pretrained("AlekseyCalvin/Custom_VAE-Z-image-FLUX.1-by-G-REPA", torch_dtype=torch.bfloat16, device_map="cuda")
-text_encoder = Qwen3ForCausalLM.from_pretrained('Qwen/Qwen3-4B-Instruct-2507').to(torch.bfloat16)
-pipeline = ZImagePipeline.from_pretrained(
-    'AlekseyCalvin/Z-Image-Deturbo-Returbo-Base_Diffusers',
-    text_encoder=text_encoder,
-    vae=vae,
-    torch_dtype=torch.bfloat16
-)
+pipeline = ZImagePipeline.from_pretrained('AlekseyCalvin/Z-Image-Deturbo-Returbo-Base_Diffusers', torch_dtype=torch.bfloat16)
+
+pipe.text_encoder = Qwen3ForCausalLM.from_pretrained('Qwen/Qwen3-4B-Instruct-2507').to(torch.bfloat16)
+pipe.vae = AutoencoderKL.from_pretrained("AlekseyCalvin/Custom_VAE-Z-image-FLUX.1-by-G-REPA", torch_dtype=torch.bfloat16, device_map="cuda")
+
 
 #pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=torch.float16).to("cuda")
 #pipe.vae = AutoencoderKL.from_pretrained("AlekseyCalvin/Custom_VAE-Z-image-FLUX.1-by-G-REPA", torch_dtype=torch.bfloat16, device_map="cuda")