Rupunct Medium

🚀 RUPunct_medium

RUPunct_medium 是 RUPunct 系列中的中等规模模型，它在性能和质量之间取得了平衡。

🚀 快速开始

RUPunct_medium 是 RUPunct 模型家族中的中等规模模型，它在性能和质量之间实现了良好的平衡。

💻 使用示例

基础用法

from transformers import pipeline
from transformers import AutoTokenizer

pt = "RUPunct/RUPunct_medium"

tk = AutoTokenizer.from_pretrained(pt, strip_accents=False, add_prefix_space=True)
classifier = pipeline("ner", model=pt, tokenizer=tk, aggregation_strategy="first")


def process_token(token, label):
    if label == "LOWER_O":
        return token
    if label == "LOWER_PERIOD":
        return token + "."
    if label == "LOWER_COMMA":
        return token + ","
    if label == "LOWER_QUESTION":
        return token + "?"
    if label == "LOWER_TIRE":
        return token + "—"
    if label == "LOWER_DVOETOCHIE":
        return token + ":"
    if label == "LOWER_VOSKL":
        return token + "!"
    if label == "LOWER_PERIODCOMMA":
        return token + ";"
    if label == "LOWER_DEFIS":
        return token + "-"
    if label == "LOWER_MNOGOTOCHIE":
        return token + "..."
    if label == "LOWER_QUESTIONVOSKL":
        return token + "?!"
    if label == "UPPER_O":
        return token.capitalize()
    if label == "UPPER_PERIOD":
        return token.capitalize() + "."
    if label == "UPPER_COMMA":
        return token.capitalize() + ","
    if label == "UPPER_QUESTION":
        return token.capitalize() + "?"
    if label == "UPPER_TIRE":
        return token.capitalize() + " —"
    if label == "UPPER_DVOETOCHIE":
        return token.capitalize() + ":"
    if label == "UPPER_VOSKL":
        return token.capitalize() + "!"
    if label == "UPPER_PERIODCOMMA":
        return token.capitalize() + ";"
    if label == "UPPER_DEFIS":
        return token.capitalize() + "-"
    if label == "UPPER_MNOGOTOCHIE":
        return token.capitalize() + "..."
    if label == "UPPER_QUESTIONVOSKL":
        return token.capitalize() + "?!"
    if label == "UPPER_TOTAL_O":
        return token.upper()
    if label == "UPPER_TOTAL_PERIOD":
        return token.upper() + "."
    if label == "UPPER_TOTAL_COMMA":
        return token.upper() + ","
    if label == "UPPER_TOTAL_QUESTION":
        return token.upper() + "?"
    if label == "UPPER_TOTAL_TIRE":
        return token.upper() + " —"
    if label == "UPPER_TOTAL_DVOETOCHIE":
        return token.upper() + ":"
    if label == "UPPER_TOTAL_VOSKL":
        return token.upper() + "!"
    if label == "UPPER_TOTAL_PERIODCOMMA":
        return token.upper() + ";"
    if label == "UPPER_TOTAL_DEFIS":
        return token.upper() + "-"
    if label == "UPPER_TOTAL_MNOGOTOCHIE":
        return token.upper() + "..."
    if label == "UPPER_TOTAL_QUESTIONVOSKL":
        return token.upper() + "?!"

while 1:
    input_text = input(":> ")
    preds = classifier(input_text)
    output = ""
    for item in preds:
        output += " " + process_token(item['word'].strip(), item['entity_group'])
    print(">>>", output)

📄 许可证

本项目采用 MIT 许可证。