import gradio as gr
from diffusers import DiffusionPipeline
import torch


pipe = DiffusionPipeline.from_pretrained(
    "segmind/tiny-sd",
    torch_dtype=torch.float32
)

pipe = pipe.to("cpu")


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

demo = gr.Interface(
    fn=generate_image,
    inputs=gr.Textbox(label="Enter Prompt"),
    outputs=gr.Image(label="Generated Image"),
    title="Tiny Stable Diffusion Demo"
)

demo.launch()