# FinePDFs-zh

**Repository Path**: hf-datasets/FinePDFs-zh

## Basic Information

- **Project Name**: FinePDFs-zh
- **Description**: Mirror of https://huggingface.co/datasets/MusubiAI/FinePDFs-zh
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-10-17
- **Last Updated**: 2025-10-17

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

---
license: odc-by
language:
- zh
- yue
task_categories:
- text-generation
size_categories:
- 1M<n<10M
pretty_name: FinePDFs-zh
configs:
    - config_name: yue
      data_files:
      - split: train
        path: data/yue/train/*
      - split: test
        path: data/yue/test/*
    - config_name: zhcn
      data_files:
      - split: train
        path: data/zhcn/train/*
      - split: test
        path: data/zhcn/test/*
    - config_name: zhcn_classical
      data_files:
      - split: train
        path: data/zhcn_classical/train/*
      - split: test
        path: data/zhcn_classical/test/*
    - config_name: zhtw
      data_files:
      - split: train
        path: data/zhtw/train/*
      - split: test
        path: data/zhtw/test/*
    - config_name: zhtw_classical
      data_files:
      - split: train
        path: data/zhtw_classical/train/*
      - split: test
        path: data/zhtw_classical/test/*
---

# FinePDFs-zh dataset card

## Introduction

**FinePDFs-zh is a fine-grained classified pdf dataset derived from the cmn_Hani subset of**  [FinePDFs](https://huggingface.co/datasets/HuggingFaceFW/finepdfs). Each sample is classified into **Traditional Chinese, Simplified Chinese, Cantonese, Classical Chinese (Traditional), and Classical Chinese (Simplified)** using [MusubiAI/ZHLID](https://huggingface.co/MusubiAI/ZHLID)**.** 

## Limitation

Data may be classified under the wrong label due to misclassification by the [MusubiAI/ZHLID](https://huggingface.co/MusubiAI/ZHLID) model. Users are encouraged to perform additional verification or processing before practical use.