Update README.md

README.md

@@ -25,7 +25,7 @@ Molecule generation example:
 >>> from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
 >>> tokenizer = AutoTokenizer.from_pretrained("zjunlp/MolGen")
->>> model = AutoModelForSeq2SeqLMq.from_pretrained("zjunlp/MolGen")
+>>> model = AutoModelForSeq2SeqLM.from_pretrained("zjunlp/MolGen")
 
 >>> sf_input = tokenizer("[C][=C][C][=C][C][=C][Ring1][=Branch1]", return_tensors="pt")
 >>> # beam search
@@ -34,8 +34,7 @@ Molecule generation example:
                               max_length=15,
                               min_length=5,
                               num_return_sequences=5,
-                              num_beams=5,
-                              past_prompt=None)
+                              num_beams=5)
 >>> sf_output = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=True).replace(" ","") for g in molecules]
 ['[C][=C][C][=C][C][=C][Ring1][=Branch1]',
 '[C][=C][C][=C][C][=C][C][=C][Ring1][=Branch1]',