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51 lines
1.2 KiB
Python
51 lines
1.2 KiB
Python
import argparse
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import glob
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from tokenizers import BertWordPieceTokenizer
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--files",
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default=None,
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metavar="path",
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type=str,
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required=True,
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help="The files to use as training; accept '**/*.txt' type of patterns \
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if enclosed in quotes",
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)
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parser.add_argument(
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"--out",
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default="./",
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type=str,
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help="Path to the output directory, where the files will be saved",
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)
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parser.add_argument(
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"--name", default="bert-wordpiece", type=str, help="The name of the output vocab files"
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)
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args = parser.parse_args()
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files = glob.glob(args.files)
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if not files:
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print(f"File does not exist: {args.files}")
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exit(1)
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# Initialize an empty tokenizer
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tokenizer = BertWordPieceTokenizer(
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clean_text=True, handle_chinese_chars=True, strip_accents=True, lowercase=True,
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)
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# And then train
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tokenizer.train(
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files,
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vocab_size=10000,
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min_frequency=2,
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show_progress=True,
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special_tokens=["[PAD]", "[UNK]", "[CLS]", "[SEP]", "[MASK]"],
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limit_alphabet=1000,
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wordpieces_prefix="##",
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)
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# Save the files
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tokenizer.save_model(args.out, args.name)
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