Upload bookcoref.py with huggingface_hub

bookcoref.py

@@ -100,7 +100,7 @@ class BookCoref(datasets.GeneratorBasedBuilder):
         self.logger = self._setup_logger()
         self.logger.info("Initializing BOOKCOREF dataset.")
         # Download nltk if not already downloaded
-        nltk.download("punkt_tab", quiet=True)
+        nltk.download("punkt", quiet=True)
         # Download and load spaCy model for tokenization if not already downloaded
         try:
             self.nlp = spacy.load("en_core_web_sm")
@@ -158,7 +158,7 @@ class BookCoref(datasets.GeneratorBasedBuilder):
         # Create console handler with a specific format
         handler = logging.StreamHandler(sys.stdout)
         formatter = logging.Formatter(
-            "[%(asctime)s][bookcoref:%(name)s][%(levelname)s] %(message)s", datefmt="%Y-%m-%d %H:%M:%S"
+            "[%(asctime)s][bookcoref][%(levelname)s] %(message)s", datefmt="%Y-%m-%d %H:%M:%S"
         )
         handler.setFormatter(formatter)
 
@@ -317,10 +317,7 @@ class BookCoref(datasets.GeneratorBasedBuilder):
         # Apply delta
         self.logger.info("Applying delta...")
         flattened_complete_sentences = flattened_downloaded_sentences + delta
-
-        self.logger.info(
-            f"Applied delta to downloaded sentences, resulting in {len(flattened_complete_sentences)} sentences."
-        )
+        self.logger.info("Applied delta to downloaded sentences.")
 
         # Reconvert back to sentences
         complete_sentences = defaultdict(list)