Update app.py

app.py

@@ -903,7 +903,7 @@ with gr.Blocks() as demo:
         with gr.Row():
             with gr.Column(scale=1):
                 prompt = gr.Textbox(label="Input your prompt here. Please enclose keywords with 'single quotes', you may refer to the examples below. The current version only supports input in English characters.", placeholder="Placeholder 'Team' hat")
-                radio = gr.Radio(["Stable Diffusion v2.1", "Stable Diffusion v1.5"], label="Pre-trained Model", value="Stable Diffusion v2.1")
+                radio = gr.Radio(["Stable Diffusion v2.1", "Stable Diffusion v1.5"], label="Pre-trained Model", value="Stable Diffusion v1.5")
                 slider_step = gr.Slider(minimum=1, maximum=50, value=20, step=1, label="Sampling step", info="The sampling step for TextDiffuser.")
                 slider_guidance = gr.Slider(minimum=1, maximum=9, value=7.5, step=0.5, label="Scale of classifier-free guidance", info="The scale of classifier-free guidance and is set to 7.5 in default.")
                 slider_batch = gr.Slider(minimum=1, maximum=4, value=4, step=1, label="Batch size", info="The number of images to be sampled. Maximum number is set to 1 for SD v2.1 to avoid OOM.")
@@ -954,7 +954,7 @@ with gr.Blocks() as demo:
             with gr.Column(scale=1):
                 prompt = gr.Textbox(label='Input your prompt here.')
                 template_image = gr.Image(label='Template image', type="pil")
-                radio = gr.Radio(["Stable Diffusion v2.1", "Stable Diffusion v1.5"], label="Pre-trained Model", value="Stable Diffusion v2.1")
+                radio = gr.Radio(["Stable Diffusion v2.1", "Stable Diffusion v1.5"], label="Pre-trained Model", value="Stable Diffusion v1.5")
                 slider_step = gr.Slider(minimum=1, maximum=50, value=20, step=1, label="Sampling step", info="The sampling step for TextDiffuser.")
                 slider_guidance = gr.Slider(minimum=1, maximum=9, value=7.5, step=0.5, label="Scale of classifier-free guidance", info="The scale of classifier-free guidance and is set to 7.5 in default.")
                 slider_batch = gr.Slider(minimum=1, maximum=4, value=4, step=1, label="Batch size", info="The number of images to be sampled. Maximum number is set to 1 for SD v2.1 to avoid OOM.")
@@ -1004,7 +1004,7 @@ with gr.Blocks() as demo:
                 with gr.Row():
                     orig_image = gr.Image(label='Original image', type="pil")
                     mask_image = gr.Image(label='Mask image', type="numpy")
-                radio = gr.Radio(["Stable Diffusion v2.1", "Stable Diffusion v1.5"], label="Pre-trained Model", value="Stable Diffusion v2.1")
+                radio = gr.Radio(["Stable Diffusion v2.1", "Stable Diffusion v1.5"], label="Pre-trained Model", value="Stable Diffusion v1.5")
                 slider_step = gr.Slider(minimum=1, maximum=50, value=20, step=1, label="Sampling step", info="The sampling step for TextDiffuser.")
                 slider_guidance = gr.Slider(minimum=1, maximum=9, value=7.5, step=0.5, label="Scale of classifier-free guidance", info="The scale of classifier-free guidance and is set to 7.5 in default.")
                 slider_batch = gr.Slider(minimum=1, maximum=4, value=4, step=1, label="Batch size", info="The number of images to be sampled. Maximum number is set to 1 for SD v2.1 to avoid OOM.")