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import streamlit as st
from diffusers import DiffusionPipeline
# Load the diffusion pipeline model
@st.cache_resource
def load_pipeline():
# Use the 'SaiRaj03/Text_To_Image' model for fast generation
pipe = DiffusionPipeline.from_pretrained("SaiRaj03/Text_To_Image")
return pipe
pipe = load_pipeline()
# Streamlit app
st.title("Text-to-Image Generation App (Fast)")
# User input for prompt
user_prompt = st.text_input("Enter your image prompt", value="Astronaut in a jungle, cold color palette, muted colors, detailed, 8k")
# Button to generate the image
if st.button("Generate Image"):
if user_prompt:
with st.spinner("Generating image..."):
# Generate the image using the new model
image = pipe(user_prompt).images[0]
# Display the generated image
st.image(image, caption="Generated Image", use_column_width=True)
else:
st.error("Please enter a valid prompt.")