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app.py

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+import streamlit as st
+from diffusers import StableDiffusionPipeline
+import torch
+import transformers
+from transformers import pipeline
+pipe = StableDiffusionPipeline.from_pretrained('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16)
+
+def generate_image(prompt):
+   
+    pipe = pipe.to("cuda")
+    
+    image = pipe(prompt).images[0]
+    return image
+
+def main():
+    st.title("Text-to-Image Generation with Stable Diffusion")
+
+    
+    prompt = st.text_input("Enter a prompt for image generation:")
+
+    if st.button("Generate Image"):
+        if prompt:
+            
+            generated_image = generate_image(prompt)
+
+            
+            st.image(generated_image, caption="Generated Image", use_column_width=True, channels="RGB")
+
+            
+            generated_image.save("generated_image.png")
+
+           
+            st.markdown(get_image_download_link(generated_image), unsafe_allow_html=True)
+
+def get_image_download_link(image):
+    """Generate a link allowing the image to be downloaded"""
+    href = f'<a href="generated_image.png" download>Click here to download the image</a>'
+    return href
+
+if __name__ == "__main__":
+    main()

requirements.txt

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+diffusers==0.25.0
+streamlit==1.20.0
+torch==2.1.2
+transformers==4.36.2