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| import streamlit as st | |
| from diffusers import StableDiffusionPipeline | |
| from PIL import Image | |
| import torch | |
| # Function to load the model | |
| def load_model(): | |
| # Replace 'your_token_here' with your actual Hugging Face token | |
| YOUR_TOKEN = "your_token_here" | |
| pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", use_auth_token=YOUR_TOKEN) | |
| return pipe | |
| # Load the model | |
| pipe = load_model() | |
| # Streamlit interface | |
| st.title("Text-to-Image Generation with Stable Diffusion") | |
| # Text input for the prompt | |
| prompt = st.text_input("Enter your prompt:") | |
| # Generate button | |
| if st.button("Generate Image"): | |
| with st.spinner('Generating image...'): | |
| # Generate image | |
| image = pipe(prompt).images[0] | |
| # Convert to PIL Image to display | |
| img = Image.fromarray(image) | |
| st.image(img, caption="Generated Image") | |