adjusted instructions for the released stable-diffusion-v1 weights

scripts/dream.py

@@ -40,7 +40,11 @@ def main():
     sys.path.append('.')
     from pytorch_lightning import logging
     from ldm.simplet2i import T2I
-
+    # these two lines prevent a horrible warning message from appearing
+    # when the frozen CLIP tokenizer is imported
+    import transformers
+    transformers.logging.set_verbosity_error()
+    
     # creating a simple text2image object with a handful of
     # defaults passed on the command line.
     # additional parameters will be added (or overriden) during

scripts/preload_models.py

@@ -2,6 +2,10 @@
 # Before running stable-diffusion on an internet-isolated machine,
 # run this script from one with internet connectivity. The
 # two machines must share a common .cache directory.
+import sys
+import transformers
+
+transformers.logging.set_verbosity_error()
 
 # this will preload the Bert tokenizer fles
 print("preloading bert tokenizer...")
@@ -10,7 +14,19 @@ tokenizer = BertTokenizerFast.from_pretrained("bert-base-uncased")
 print("...success")
 
 # this will download requirements for Kornia
-print("preloading Kornia requirements...")
+print("preloading Kornia requirements (ignore the warnings)...")
 import kornia
 print("...success")
 
+# doesn't work - probably wrong logger
+# logging.getLogger('transformers.tokenization_utils').setLevel(logging.ERROR)
+version='openai/clip-vit-large-patch14'
+
+print('preloading CLIP model (Ignore the warnings)...')
+sys.stdout.flush()
+import clip
+from transformers import CLIPTokenizer, CLIPTextModel
+tokenizer  =CLIPTokenizer.from_pretrained(version)
+transformer=CLIPTextModel.from_pretrained(version)
+print('\n\n...success')
+