Update README.md

README.md

@@ -24,50 +24,9 @@ Task: Summarization
 ```python
 from transformers import PegasusForConditionalGeneration,BertTokenizer
 from typing import List, Optional
-
-# Need to download tokenizers_pegasus.py and other Python script from Fengshenbang-LM github repo in advance,
-# or you can mv download in tokenizers_pegasus.py and data_utils.py in https://huggingface.co/IDEA-CCNL/Randeng_Pegasus_523M_Summary/tree/main
-# Strongly recommend you git clone the Fengshenbang-LM repo:
-# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
-# 2. cd Fengshenbang-LM/fengshen/examples/pegasus/
-# and then you will see the tokenizers_pegasus.py and data_utils.py which are needed by pegasus model
-# from tokenizers_pegasus import PegasusTokenizer
-class PegasusTokenizer(BertTokenizer):
-    model_input_names = ["input_ids", "attention_mask"]
-    def __init__(self, **kwargs):
-        super().__init__(**kwargs)
-        self.add_special_tokens({'additional_special_tokens':["<mask_1>"]})
-
-    def build_inputs_with_special_tokens(
-            self,
-            token_ids_0: List[int],
-            token_ids_1: Optional[List[int]] = None) -> List[int]:
-
-        if token_ids_1 is None:
-            return token_ids_0 + [self.eos_token_id]
-        return token_ids_0 + token_ids_1 + [self.eos_token_id]
-
-    def _special_token_mask(self, seq):
-        all_special_ids = set(
-            self.all_special_ids)  # call it once instead of inside list comp
-        # all_special_ids.remove(self.unk_token_id)  # <unk> is only sometimes special
-        return [1 if x in all_special_ids else 0 for x in seq]
-
-    def get_special_tokens_mask(
-            self,
-            token_ids_0: List[int],
-            token_ids_1: Optional[List[int]] = None,
-            already_has_special_tokens: bool = False) -> List[int]:
-        if already_has_special_tokens:
-            return self._special_token_mask(token_ids_0)
-        elif token_ids_1 is None:
-            return self._special_token_mask(token_ids_0) + [self.eos_token_id]
-        else:
-            return self._special_token_mask(token_ids_0 +
-                                            token_ids_1) + [self.eos_token_id]
                                             
 model = PegasusForConditionalGeneration.from_pretrained('dongxq/test_model')
-tokenizer = PegasusTokenizer.from_pretrained('dongxq/test_model')
+tokenizer = BertTokenizer.from_pretrained('dongxq/test_model')
 
 text = "在北京冬奥会自由式滑雪女子坡面障碍技巧决赛中，中国选手谷爱凌夺得银牌。祝贺谷爱凌！今天上午，自由式滑雪女子坡面障碍技巧决赛举行。决赛分三轮进行，取选手最佳成绩排名决出奖牌。第一跳，中国选手谷爱凌获得69.90分。在12位选手中排名第三。完成动作后，谷爱凌又扮了个鬼脸，甚是可爱。第二轮中，谷爱凌在道具区第三个障碍处失误，落地时摔倒。获得16.98分。网友：摔倒了也没关系，继续加油！在第二跳失误摔倒的情况下，谷爱凌顶住压力，第三跳稳稳发挥，流畅落地！获得86.23分！此轮比赛，共12位选手参赛，谷爱凌第10位出场。网友：看比赛时我比谷爱凌紧张，加油！"
 inputs = tokenizer(text, max_length=512, return_tensors="pt")