use pre-commit

Former-commit-id: 7cfede95df22a9ff236788f04159b6b16b8d04bb

data/alpaca_en_demo.json

@@ -4999,4 +4999,4 @@
     "input": "Time waits for no one.",
     "output": "No one can stop time from moving forward."
   }
-]
+]

data/alpaca_zh_demo.json

@@ -4999,4 +4999,4 @@
     "input": "",
     "output": "安第斯山脉位于南美洲，横跨七个国家，包括委内瑞拉，哥伦比亚，厄瓜多尔，秘鲁，玻利维亚，智利和阿根廷。安第斯山脉是世界上最长的山脉之一，全长约7,000千米（4,350英里），其山脉沿着南美洲西海岸蜿蜒延伸，平均海拔约为4,000米（13,000英尺）。在其南部，安第斯山脉宽度达到700千米（430英里），在其北部宽度约为500千米（310英里）。"
   }
-]
+]

data/belle_multiturn/belle_multiturn.py

@@ -17,9 +17,9 @@ _CITATION = """\
 }
 """
 
-_HOMEPAGE = "{}/datasets/BelleGroup/multiturn_chat_0.8M".format(_HF_ENDPOINT)
+_HOMEPAGE = f"{_HF_ENDPOINT}/datasets/BelleGroup/multiturn_chat_0.8M"
 _LICENSE = "gpl-3.0"
-_URL = "{}/datasets/BelleGroup/multiturn_chat_0.8M/resolve/main/multiturn_chat_0.8M.json".format(_HF_ENDPOINT)
+_URL = f"{_HF_ENDPOINT}/datasets/BelleGroup/multiturn_chat_0.8M/resolve/main/multiturn_chat_0.8M.json"
 
 
 class BelleMultiturn(datasets.GeneratorBasedBuilder):
@@ -38,7 +38,7 @@ class BelleMultiturn(datasets.GeneratorBasedBuilder):
         return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": file_path})]
 
     def _generate_examples(self, filepath: str):
-        with open(filepath, "r", encoding="utf-8") as f:
+        with open(filepath, encoding="utf-8") as f:
             for key, row in enumerate(f):
                 data = json.loads(row)
                 conversations = []

data/dataset_info.json

@@ -625,4 +625,4 @@
     },
     "folder": "python"
   }
-}
+}

data/dpo_zh_demo.json

@@ -5055,4 +5055,4 @@
       "value": "C. 参与讨论"
     }
   }
-]
+]

data/glaive_toolcall_en_demo.json

@@ -9155,4 +9155,4 @@
     ],
     "tools": "[]"
   }
-]
+]

data/glaive_toolcall_zh_demo.json

@@ -9019,4 +9019,4 @@
     ],
     "tools": "[]"
   }
-]
+]

data/hh_rlhf_en/hh_rlhf_en.py

@@ -8,9 +8,9 @@ import datasets
 _HF_ENDPOINT = os.getenv("HF_ENDPOINT", "https://huggingface.co")
 _DESCRIPTION = "Human preference data about helpfulness and harmlessness."
 _CITATION = ""
-_HOMEPAGE = "{}/datasets/Anthropic/hh-rlhf".format(_HF_ENDPOINT)
+_HOMEPAGE = f"{_HF_ENDPOINT}/datasets/Anthropic/hh-rlhf"
 _LICENSE = "mit"
-_URL = "{}/datasets/Anthropic/hh-rlhf/resolve/main/".format(_HF_ENDPOINT)
+_URL = f"{_HF_ENDPOINT}/datasets/Anthropic/hh-rlhf/resolve/main/"
 _URLS = {
     "train": [
         _URL + "harmless-base/train.jsonl.gz",
@@ -53,7 +53,7 @@ class HhRlhfEn(datasets.GeneratorBasedBuilder):
     def _generate_examples(self, filepaths: List[str]):
         key = 0
         for filepath in filepaths:
-            with open(filepath, "r", encoding="utf-8") as f:
+            with open(filepath, encoding="utf-8") as f:
                 for row in f:
                     data = json.loads(row)
                     chosen = data["chosen"]

data/identity.json

@@ -454,4 +454,4 @@
     "input": "",
     "output": "抱歉，我不是 OpenAI 开发的 ChatGPT，我是 {{author}} 开发的 {{name}}，旨在为用户提供智能化的回答和帮助。"
   }
-]
+]

data/kto_en_demo.json

@@ -5395,4 +5395,4 @@
     ],
     "label": false
   }
-]
+]

data/mllm_demo.json

@@ -137,4 +137,4 @@
       "mllm_demo_data/3.jpg"
     ]
   }
-]
+]

data/mllm_video_demo.json

@@ -44,4 +44,4 @@
       "mllm_demo_data/3.mp4"
     ]
   }
-]
+]

data/ultra_chat/ultra_chat.py

@@ -20,9 +20,9 @@ _CITATION = """\
 }
 """
 
-_HOMEPAGE = "{}/datasets/stingning/ultrachat".format(_HF_ENDPOINT)
+_HOMEPAGE = f"{_HF_ENDPOINT}/datasets/stingning/ultrachat"
 _LICENSE = "cc-by-nc-4.0"
-_BASE_DATA_URL = "{}/datasets/stingning/ultrachat/resolve/main/train_{{idx}}.jsonl".format(_HF_ENDPOINT)
+_BASE_DATA_URL = f"{_HF_ENDPOINT}/datasets/stingning/ultrachat/resolve/main/train_{{idx}}.jsonl"
 
 
 class UltraChat(datasets.GeneratorBasedBuilder):
@@ -42,7 +42,7 @@ class UltraChat(datasets.GeneratorBasedBuilder):
 
     def _generate_examples(self, filepaths: List[str]):
         for filepath in filepaths:
-            with open(filepath, "r", encoding="utf-8") as f:
+            with open(filepath, encoding="utf-8") as f:
                 for row in f:
                     try:
                         data = json.loads(row)