Add a Guidance Scale parameter

app.py

@@ -50,26 +50,27 @@ with gr.Blocks() as demo:
                 # steps = gr.Slider(label="Inference Steps", minimum=1, maximum=8, step=1, value=1, interactive=True)
                 # eta = gr.Number(label="Eta (Corresponds to parameter eta (η) in the DDIM paper, i.e. 0.0 eqauls DDIM, 1.0 equals LCM)", value=1., interactive=True)
                 prompt = gr.Text(label="Prompt", value="a photo of a cat", interactive=True)
+                guidance_scale = gr.Slider(minimum = 0, maximum = 13, value = 0, step = 0.1, label = "Classifier-Free Guidance Scale", info = "lower=image quality, higher=follow the prompt", interactive=True)
                 seed = gr.Number(label="Seed", value=3413, interactive=True)
                 btn = gr.Button(value="run")
             with gr.Column():
                 output = gr.Gallery(height=1024)
 
             @spaces.GPU
-            def process_image(num_images, height, width, prompt, seed):
+            def process_image(num_images, height, width, prompt, guidance_scale, seed):
                 global pipe
                 with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16), timer("inference"):
                     return pipe(
                         prompt=[prompt]*num_images,
                         generator=torch.Generator().manual_seed(int(seed)),
                         num_inference_steps=1,
-                        guidance_scale=0.,
+                        guidance_scale=guidance_scale,
                         height=int(height),
                         width=int(width),
                         timesteps=[800]
                     ).images
 
-            reactive_controls = [num_images, height, width, prompt, seed]
+            reactive_controls = [num_images, height, width, prompt, guidance_scale, seed]
 
             # for control in reactive_controls:
             #     control.change(fn=process_image, inputs=reactive_controls, outputs=[output])