Make it slimmer

app.py

@@ -23,7 +23,7 @@ import torchvision.transforms.functional as TF
 import clip
 import unicodedata
 import re
-from tqdm.notebook import tqdm
+from tqdm import tqdm
 from torchvision.transforms import Compose, Resize, ToTensor, Normalize
 from IPython.display import display
 from einops import rearrange
@@ -116,7 +116,7 @@ def embed_url(url):
 
 class CLIP(object):
   def __init__(self):
-    clip_model = "ViT-B/16"
+    clip_model = "ViT-B/32"
     self.model, _ = clip.load(clip_model)
     self.model = self.model.requires_grad_(False)
     self.normalize = transforms.Normalize(mean=[0.48145466, 0.4578275, 0.40821073],
@@ -203,8 +203,8 @@ def run(prompt,steps,model):
         ]
     )
 
-    initial_batch = 4  # actually that will be multiplied by initial_image_steps
-    initial_image_steps = 32
+    initial_batch = 2  # actually that will be multiplied by initial_image_steps
+    initial_image_steps = 16
 
     def get_image(timestring):
         os.makedirs(f"samples/{timestring}", exist_ok=True)