Update app.py

app.py

@@ -51,16 +51,17 @@ 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)
-qwen_path = 'nightknocker/recurrent-qwen3-z-image-turbo'
-text_encoder = Qwen3ForCausalLM.from_pretrained(qwen_path).to(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
 )
 
 #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")
+pipe.vae = AutoencoderKL.from_pretrained("AlekseyCalvin/Custom_VAE-Z-image-FLUX.1-by-G-REPA", torch_dtype=torch.bfloat16, device_map="cuda")
 
 #custom_vae = AutoencoderKL.from_pretrained("AlekseyCalvin/AnimeVAE_by_Anzhc_for_Flux_ZiT", torch_dtype=torch.float32, ignore_mismatched_sizes=True, low_cpu_mem_usage=False, device_map=None)