Update README.md

README.md

@@ -34,7 +34,7 @@ DIPPER ("**Di**scourse **P**ara**p**hras**er**") is a 11B parameter paraphrase g
 
 We leverage the PAR3 dataset publicly released by Thai et al. (2022) to train DIPPER. This dataset contains multiple translations of non-English novels into English aligned at a paragraph level (e.g., it contains both the Henry Morley and Robert Adams translations of Voltaire’s Candide), which we treat as paragraphlevel paraphrases and use to train our paraphraser.
 
-## Using DIPPER
+## Using DIPPER (no-context)
 
 Full instructions: https://github.com/martiansideofthemoon/ai-detection-paraphrases#running-the-paraphraser-model-dipper
 
@@ -72,8 +72,7 @@ class DipperParaphraser(object):
 
         for sent_idx in range(0, len(sentences), sent_interval):
             curr_sent_window = " ".join(sentences[sent_idx:sent_idx + sent_interval])
-            final_input_text = f"lexical = {lex_code}, order = {order_code}"
-            final_input_text += f" <sent> {curr_sent_window} </sent>"
+            final_input_text = f"lexical = {lex_code}, order = {order_code} {curr_sent_window}"
 
             final_input = self.tokenizer([final_input_text], return_tensors="pt")
             final_input = {k: v.cuda() for k, v in final_input.items()}