Update app.py

app.py

@@ -26,12 +26,13 @@ pipe = StableDiffusionXLControlNetPipeline.from_pretrained(
     variant="fp16",
     use_safetensors=True
 )
+pipe.to("cuda")
 
 custom_model = "fffiloni/eugene_jour_general"
 
 # This is where you load your trained weights
 pipe.load_lora_weights(custom_model, use_auth_token=True)
-pipe.to("cuda")
+
 #pipe.enable_model_cpu_offload()
 
 def infer(image_in, prompt, controlnet_conditioning_scale, guidance_scale):
@@ -48,13 +49,16 @@ def infer(image_in, prompt, controlnet_conditioning_scale, guidance_scale):
     image = np.concatenate([image, image, image], axis=2)
     image = Image.fromarray(image)
 
+    lora_scale= 0.9
+    
     images = pipe(
         prompt, 
         negative_prompt=negative_prompt, 
         image=image, 
         controlnet_conditioning_scale=controlnet_conditioning_scale,
         guidance_scale = guidance_scale,
-        num_inference_steps=50
+        num_inference_steps=50,
+        cross_attention_kwargs={"scale": lora_scale}
         ).images
 
     images[0].save(f"hug_lab.png")