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# Import necessary libraries | |
import streamlit as st | |
import torch | |
from diffusers import StableDiffusionXLPipeline | |
# Load the stable diffusion model | |
pipe = StableDiffusionXLPipeline.from_pretrained( | |
"stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16 | |
) | |
pipe = pipe.to("cpu") # Move the model to CPU for processing | |
# Create a Streamlit app | |
st.title("Stable Diffusion XL Image Generation") | |
# Add a text input for the prompt | |
prompt = st.text_area("Enter your prompt here", "Type your prompt here...") | |
# Add an info text to provide guidance | |
st.markdown("This app uses Stable Diffusion XL to generate an image based on the given prompt.") | |
# Generate the image based on the prompt | |
if st.button("Generate"): | |
with st.spinner("Generating..."): # Display a spinner while generating the image | |
try: | |
# Use the model to generate the image | |
image = pipe(prompt).images[0] | |
# Display the generated image | |
st.image(image, caption="Generated Image", use_column_width=True) | |
except Exception as e: | |
st.error(f"An error occurred: {e}") | |