Do not use torch_dtype=torch.float16

app.py

@@ -15,7 +15,7 @@ def generate(
     generator = torch.manual_seed(seed)
 
     if input_image is None:
-        pipeline = DiffusionPipeline.from_pretrained("Lykon/DreamShaper", torch_dtype=torch.float16)
+        pipeline = DiffusionPipeline.from_pretrained("Lykon/DreamShaper")
 
         return pipeline(
             prompt=prompt,
@@ -32,8 +32,8 @@ def generate(
     image = np.concatenate([image, image, image], axis=2)
     canny_image = Image.fromarray(image)
 
-    controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-canny", torch_dtype=torch.float16)
-    pipeline = StableDiffusionControlNetPipeline.from_pretrained("Lykon/DreamShaper", controlnet=controlnet, torch_dtype=torch.float16)
+    controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-canny")
+    pipeline = StableDiffusionControlNetPipeline.from_pretrained("Lykon/DreamShaper", controlnet=controlnet)
 
     return pipeline(
         prompt=prompt,
@@ -57,6 +57,7 @@ iface = gr.Interface(
         gr.Slider(label="CFG Scale", minimum=1, maximum=30, value=9, step=0.5),
         gr.Slider(
             label="Seed",
+            info="Refresh the page to generate a new random seed.",
             minimum=0,
             maximum=4294967294,
             step=1,