yys/OpenOrca-Chinese

---
license: mit
task_categories:
- conversational
- text-classification
- token-classification
- table-question-answering
- question-answering
- zero-shot-classification
- summarization
- feature-extraction
- text-generation
- text2text-generation
language:
- zh
pretty_name: OpenOrca-Chinese
size_categories:
- 10M<n<100M
---
<p><h1>🐋 OpenOrca-Chinese 数据集！🐋</h1></p>

感谢 [Open-Orca/OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca) 数据集的发布，给广大NLP研究人员和开发者带来了宝贵的资源！

这是一个对 [Open-Orca/OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca) 数据集中文翻译的版本，翻译引擎为 Google 翻译，希望能给中文 LLM 研究做出一点点贡献。

<br/>

# Dataset Summary

The OpenOrca dataset is a collection of augmented [FLAN Collection data](https://arxiv.org/abs/2301.13688).
Currently ~1M GPT-4 completions, and ~3.2M GPT-3.5 completions.
It is tabularized in alignment with the distributions presented in the ORCA paper and currently represents a partial completion of the full intended dataset, with ongoing generation to expand its scope.
The data is primarily used for training and evaluation in the field of natural language processing.

<a name="dataset-structure"></a>

# Dataset Structure

<a name="data-instances"></a>

## Data Instances

A data instance in this dataset represents entries from the FLAN collection which have been augmented by submitting the listed question to either GPT-4 or GPT-3.5.
The response is then entered into the response field.

<a name="data-fields"></a>

## Data Fields

The fields are:
1) 'id', a unique numbered identifier which includes one of 'niv', 't0', 'cot', or 'flan' to represent which source FLAN Collection submix the 'question' is sourced from.
2) 'system_prompt', representing the System Prompt presented to the GPT-3.5 or GPT-4 API for the datapoint
3) 'question', representing a question entry as provided by the FLAN Collection
4) 'response', a response to that question received from a query to either GPT-3.5 or GPT-4.

原始信息汇总

数据集概述

基本信息

• 许可证: MIT
• 任务类别:
  • 对话
  • 文本分类
  • 令牌分类
  • 表格问答
  • 问答
  • 零样本分类
  • 摘要
  • 特征提取
  • 文本生成
  • 文本到文本生成
• 语言: 中文
• 大小类别: 10M<n<100M

数据集描述

• 名称: OpenOrca-Chinese
• 来源: 基于 Open-Orca/OpenOrca 数据集的中文翻译版本
• 翻译引擎: Google 翻译
• 原始数据: 来自 FLAN Collection 数据的增强集合
• 当前数据量: 约1M GPT-4完成，约3.2M GPT-3.5完成
• 数据用途: 主要用于自然语言处理领域的训练和评估

数据集结构

数据实例

• 描述: 每个数据实例代表来自FLAN集合的条目，通过向GPT-4或GPT-3.5提交列出的问题进行增强，并将响应输入到响应字段中。

数据字段

• id: 唯一编号标识符，包括niv, t0, cot, 或 flan之一，表示问题来源的FLAN集合子混合。
• system_prompt: 向GPT-3.5或GPT-4 API呈现的系统提示。
• question: 来自FLAN集合的问题条目。
• response: 通过查询GPT-3.5或GPT-4收到的对该问题的响应。