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A Chinese relation extraction data utility toolkit based on CasRel model

Project description

CasRel 数据处理工具包

这是一个基于 CasRel 模型的中文关系抽取数据处理工具包,支持 BERT 预训练模型。

支持的 BERT 模型

  • bert-base-chinese: 默认中文 BERT 基础模型,适用于通用中文任务,参数量适中,bert_dim=768。

安装

  • pip install casrel_datautils

使用示例

以下是一个使用 casrel_datautils 进行数据加载和单条样本处理的示例代码:

from casrel_datautils.Base_Conf import BaseConfig
from casrel_datautils.data_loader import get_dataloader
from casrel_datautils.process import single_sample_process

# 配置基础参数
baseconf = BaseConfig(
    bert_path_or_bertModel_name="bert-base-chinese", #模型路径或模型名称
    train_data=r"本地数据路径train.json",
    test_data=r"本地数据路径test.json",
    rel_data=r"本地关系数据路径relation.json",
    batch_size=2
)

# 获取数据加载器
dataloaders = get_dataloader(baseconf)

# 单条样本处理
sample = {"text": "这是一个测试句子"}
input_tensor, mask_tensor = single_sample_process(baseconf, sample)
print(input_tensor.shape)
print(mask_tensor.shape)

说明

  • BaseConfig: 用于设置 BERT 模型路径、数据路径和批次大小等参数。
  • get_dataloader: 返回训练、验证和测试的数据加载器。
  • single_sample_process: 处理单条文本样本,返回输入张量和掩码张量。

注意事项

  • 确保数据文件(如 train.jsontest.jsonrelation.json)路径正确。
  • 根据任务需求选择合适的 BERT 模型。

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