gradio_app.py

import gradio as gr
from diffusers import StableDiffusionXLPipeline
import torch

pipe = StableDiffusionXLPipeline.from_pretrained(
    "segmind/SSD-1B", 
    torch_dtype=torch.float16, 
    use_safetensors=True, 
    variant="fp16"
)
pipe.to("cuda")

def generate_image(prompt, neg_prompt):
    image = pipe(
        prompt=prompt, 
        negative_prompt=neg_prompt
    ).images[0]
    return image

prompt = gr.Text(
                label="Prompt",
                show_label=False,
                max_lines=1,
                placeholder="Enter your prompt",
                container=False,
            )
neg_prompt = gr.Text(
                label="Negative Prompt",
                show_label=False,
                max_lines=1,
                placeholder="Enter your negative prompt",
                container=False,
            )

iface = gr.Interface(
    fn=generate_image,
    inputs=[prompt, neg_prompt],
    outputs="image",
    title="Text to Image Generation",
    examples=[
        ["a painting of a cute cat sitting on a chair", "ugly, blurry"],
        ["an astronaut riding a horse on mars", "poorly drawn"]
    ],
    allow_flagging=False
)

iface.launch(share=True)