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import gradio as gr
from gradio_client import Client
def generate_image(prompt, negative_prompt, seed, width, height, prior_inference_steps, prior_guidance_scale, decoder_inference_steps, decoder_guidance_scale, num_images):
client = Client("multimodalart/stable-cascade")
result = client.predict(
prompt,
negative_prompt,
0, # float (numeric value between 0 and 2147483647) in 'Seed' Slider component
1024, # float (numeric value between 1024 and 1536) in 'Width' Slider component
1024, # float (numeric value between 1024 and 1536) in 'Height' Slider component
10, # float (numeric value between 10 and 30) in 'Prior Inference Steps' Slider component
0, # float (numeric value between 0 and 20) in 'Prior Guidance Scale' Slider component
4, # float (numeric value between 4 and 12) in 'Decoder Inference Steps' Slider component
0, # float (numeric value between 0 and 0) in 'Decoder Guidance Scale' Slider component
1, # float (numeric value between 1 and 2) in 'Number of Images' Slider component
api_name="/run"
)
return result
demo = gr.Interface(
fn=generate_image,
inputs=[
gr.Textbox(label="Prompt"),
gr.Textbox(label="Negative prompt", value="bad quality, low quality"),
],
outputs=["image"],
theme = "soft"
)
demo.launch()
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