size_categories:10K<n<100K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
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---

Here is the README content in a plain text format that you can easily copy and paste:

---

# Dataset: Combined Chinese QA Dataset for Meta-LLaMA Fine-tuning

## Overview

This dataset has been created by combining multiple datasets with the objective of fine-tuning the `meta-llama/Meta-Llama-3.1-8B` model for learning Question-Answering (QA) tasks in Chinese.

## Sources

The dataset is composed of the following sources:

1. **LooksJuicy/ruozhiba**  
   A dataset designed for Chinese language QA tasks.

2. **COIG-CQIA**  
   [Download Link](https://huggingface.co/datasets/m-a-p/COIG-CQIA/resolve/main/ruozhiba/ruozhiba_ruozhiba.jsonl)  
   Another Chinese QA dataset that provides a wide variety of question-answer pairs.

3. **Chinese LLaMA-Alpaca**  
   [Download Link](https://raw.githubusercontent.com/ymcui/Chinese-LLaMA-Alpaca/main/data/alpaca_data_zh_51k.json)  
   A Chinese adaptation of the Alpaca dataset tailored for instructional fine-tuning.

## Purpose

This combined dataset is specifically intended for fine-tuning the `meta-llama/Meta-Llama-3.1-8B` model. The fine-tuned model is aimed at enhancing its capability in understanding and generating responses to Chinese QA tasks.

## Usage

To load the dataset, you can use the following code:

```python
from datasets import load_dataset

dataset = load_dataset("path/to/your/combined/dataset")
```

