Update app.py

app.py

@@ -27,10 +27,10 @@ DEFAULT_WIDTH = 1024
 
 REPO = "sd-community/sdxl-flash"
 
-vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse-original").half().to(DEVICE)
+#vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse-original").half().to(DEVICE), vae=vae
 controlnet = ControlNetModel.from_pretrained("MakiPan/controlnet-encoded-hands-130k", torch_dtype=torch.float16)
 
-model = StableDiffusionXLPipeline.from_pretrained(REPO, vae=vae, controlnet=controlnet, torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False)
+model = StableDiffusionXLPipeline.from_pretrained(REPO, controlnet=controlnet, torch_dtype=torch.float16, use_safetensors=True, add_watermarker=False)
 model.load_lora_weights("ehristoforu/dalle-3-xl-v2", adapter_name="base")
 model.set_adapters(["base"], adapter_weights=[0.7])
 model.to(DEVICE)
@@ -73,7 +73,7 @@ def generate(input=DEFAULT_INPUT, negative_input=DEFAULT_NEGATIVE_INPUT, height=
         "guidance_scale": guidance,
         "num_images_per_prompt": number,
         "controlnet_conditioning_scale": 1,
-        "cross_attention_kwargs": {"scale": 1},
+        "cross_attention_kwargs": {"scale": 0.1},
         "generator": torch.Generator().manual_seed(seed),
         "use_resolution_binning": True,
         "output_type":"pil",