Upload 4 files

app.py

@@ -4,7 +4,7 @@ import pdb
 from options import get_parser_main_model
 
 opts = get_parser_main_model().parse_args()
-model = watermark_model(language=opts.language, mode=opts.mode, tau_word=opts.tau_word, lamda=opts.lamda)
+model = watermark_model(language='English', mode=opts.mode, tau_word=0.8, lamda=0.83)
 def watermark_embed_demo(raw):
 
     watermarked_text = model.embed(raw)
@@ -54,4 +54,4 @@ with demo:
 if __name__ == "__main__":
     gr.close_all()
     demo.title = "Watermarking Text Generated by Black-Box Language Models"
-    demo.launch(share = True, server_port=8899)
+    demo.launch()

models/watermark_faster.py

@@ -8,8 +8,8 @@ import hashlib
 from scipy.stats import norm
 import gensim
 import pdb
-from transformers import BertForMaskedLM as WoBertForMaskedLM
-from wobert import WoBertTokenizer
+# from transformers import BertForMaskedLM as WoBertForMaskedLM
+# from wobert import WoBertTokenizer
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
 from transformers import BertForMaskedLM, BertTokenizer, RobertaForSequenceClassification, RobertaTokenizer