Update app.py

app.py

@@ -4,7 +4,7 @@ import gradio as gr
 import spaces
 
 # Load the pre-trained diffusion model
-pipe = StableDiffusion3Pipeline.from_pretrained('ptx0/sd3-diffusion-vpred-zsnr', torch_dtype=torch.bfloat16)
+pipe = StableDiffusion3Pipeline.from_pretrained('ptx0/sd3-reality-mix', torch_dtype=torch.bfloat16)
 pipe.to('cuda')
 import re
 
@@ -19,13 +19,12 @@ def extract_resolution(resolution_str):
 
 # Define the image generation function with adjustable parameters and a progress bar
 @spaces.GPU
-def generate(prompt, guidance_scale, guidance_rescale, num_inference_steps, resolution, negative_prompt):
+def generate(prompt, guidance_scale, num_inference_steps, resolution, negative_prompt):
     width, height = extract_resolution(resolution) or (1024, 1024)
     return pipe(
         prompt,
         negative_prompt=negative_prompt,
         guidance_scale=guidance_scale,
-        #guidance_rescale=guidance_rescale,
         num_inference_steps=num_inference_steps,
         width=width, height=height
     ).images
@@ -43,7 +42,6 @@ iface = gr.Interface(
     inputs=[
         gr.Text(label="Enter your prompt"),
         gr.Slider(1, 20, step=0.1, label="Guidance Scale", value=9.5),
-        gr.Slider(0, 1, step=0.1, label="Rescale classifier-free guidance", value=0.7),
         gr.Slider(1, 50, step=1, label="Number of Inference Steps", value=25),
         gr.Radio(["1024x1024", "1152x960", "896x1152"], label="Resolution", value="1152x960"),
         gr.Text(value="underexposed, blurry, ugly, washed-out", label="Negative Prompt")