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remote_formatter

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远程格式化器。用于从huggingface hub的存储库加载数据集。 本SKILL使用依赖data_juicer，请在调用前安装好python环境并安装data_juicer，你可用以下指令进行安装： pip install py-data-juicer 当用户提到加载HuggingFace数据集、远程数据集加载、HuggingFace Hub等需求时使用此skill。

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功能概述

该算子用于从 HuggingFace Hub 加载数据集，支持加载公开数据集和需要认证的私有数据集。

核心参数

参数类型必填默认值说明
dataset_pathstring是-HuggingFace数据集路径
output_pathstring是-输出JSONL文件路径
text_keyslist否['text']文本字段名列表
splitstring否'train'数据集划分
num_procint否1并行处理的进程数

输入数据格式

dataset_path 支持以下格式：

  • 公开数据集：username/dataset_name
  • 本地路径或远程路径

输出数据格式

输出为 JSONL 格式，每行一个样本。

使用示例

命令行调用

# 加载HuggingFace公开数据集
python scripts/run_remote_formatter.py \
  --dataset_path "rotten_tomatoes" \
  --output_path /path/to/output.jsonl

# 指定文本字段
python scripts/run_remote_formatter.py \
  --dataset_path "yelp_review_full" \
  --output_path /path/to/output.jsonl \
  --text_keys text \
  --split train

# 带认证加载私有数据集
python scripts/run_remote_formatter.py \
  --dataset_path "private_user/private_dataset" \
  --output_path /path/to/output.jsonl

参数说明

  • --dataset_path: HuggingFace数据集路径
  • --output_path: 输出JSONL文件路径
  • --text_keys: 文本字段名，可重复指定多个（默认 ['text']）
  • --split: 数据集划分（默认 'train'）
  • --num_proc: 并行进程数，默认1

注意事项

  1. 首次运行会下载数据集，可能需要较长时间
  2. 对于私有数据集，需要先登录 HuggingFace：huggingface-cli login
  3. 支持的数据集格式由 HuggingFace datasets 库决定