Update app.py

app.py

@@ -26,8 +26,10 @@ def ask(input_im, scale, steps, seed, images):
 def main(input_im, scale, steps, seed):
     
     images = []
-    images = ask(input_im, scale, n_samples, steps, seed, images)
-    images = ask(input_im, scale, n_samples, steps, seed, images)
+    for i in range(2):
+        images = ask(input_im, scale, n_samples, steps, seed, images)
+    #images = ask(input_im, scale, n_samples, steps, seed, images)
+    #images = ask(input_im, scale, n_samples, steps, seed, images)
     
     return images
 
@@ -49,20 +51,18 @@ output.style(grid=2, height="")
 
 description = \
 """
-<p style='text-align: center;'>This demo is running on CPU. Working version fixed by Sylvain <a href='https://twitter.com/fffiloni' target='_blank'>@fffiloni</a>. You'll get 4 images variations. NSFW filters enabled.<img id='visitor-badge' alt='visitor badge' src='https://visitor-badge.glitch.me/badge?page_id=gradio-blocks.sd-img-variations' style='display: inline-block' /><br />
+<p style='text-align: center;'>This demo is running on CPU. Working version fixed by Sylvain <a href='https://twitter.com/fffiloni' target='_blank'>@fffiloni</a>. You'll get 4 images variations. NSFW filters enabled. <img id='visitor-badge' alt='visitor badge' src='https://visitor-badge.glitch.me/badge?page_id=gradio-blocks.sd-img-variations' style='display: inline-block' /><br />
 Generate variations on an input image using a fine-tuned version of Stable Diffusion.<br />
 Trained by <a href='https://www.justinpinkney.com' target='_blank'>Justin Pinkney</a> (<a href='https://twitter.com/Buntworthy' target='_blank'>@Buntworthy</a>) at <a href='https://lambdalabs.com/' target='_blank'>Lambda</a><br />
 This version has been ported to 🤗 Diffusers library, see more details on how to use this version in the <a href='https://github.com/LambdaLabsML/lambda-diffusers' target='_blank'>Lambda Diffusers repo</a>.<br />
-
 For the original training code see <a href='https://github.com/justinpinkney/stable-diffusion' target='_blank'>this repo</a>.
-<img src='https://raw.githubusercontent.com/justinpinkney/stable-diffusion/main/assets/im-vars-thin.jpg'/>
-
+<img src='https://raw.githubusercontent.com/justinpinkney/stable-diffusion/main/assets/im-vars-thin.jpg' />
 </p>
 """
 
 article = \
 """
-
+—
 ## How does this work?
 The normal Stable Diffusion model is trained to be conditioned on text input. This version has had the original text encoder (from CLIP) removed, and replaced with
 the CLIP _image_ encoder instead. So instead of generating images based a text input, images are generated to match CLIP's embedding of the image.