Update app.py

app.py

@@ -18,6 +18,8 @@ pipe = DiffusionPipeline.from_pretrained(
 
 device="cuda" if torch.cuda.is_available() else "cpu"
 
+pipe.to(device)
+
 def load_model(custom_model, weight_name):
     
     if custom_model == "":
@@ -26,7 +28,6 @@ def load_model(custom_model, weight_name):
     
     # This is where you load your trained weights
     pipe.load_lora_weights(custom_model, weight_name=weight_name, use_auth_token=True)
-    pipe.to(device)
     
     return "Model loaded!"
 
@@ -37,7 +38,7 @@ def infer (prompt, inf_steps, guidance_scale, seed, lora_weight, progress=gr.Pro
     image = pipe(
         prompt=prompt, 
         num_inference_steps=inf_steps,
-        guidance_scale = float(guidance_scale),
+        guidance_scale = guidance_scale,
         generator=generator,
         cross_attention_kwargs={"scale": lora_weight}
     ).images[0]