task_categories:conversational task_categories:text-classification task_categories:token-classification task_categories:table-question-answering task_categories:question-answering task_categories:zero-shot-classification task_categories:summarization task_categories:feature-extraction task_categories:text-generation task_categories:text2text-generation size_categories:10M<n<100M language:zh license:mit arxiv:2301.13688 region:us
---
language:
- zh
license: mit
size_categories:
- 10M<n<100M
task_categories:
- conversational
- text-classification
- token-classification
- table-question-answering
- question-answering
- zero-shot-classification
- summarization
- feature-extraction
- text-generation
- text2text-generation
pretty_name: OpenOrca-Chinese
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: id
    dtype: string
  - name: system_prompt
    dtype: string
  - name: question
    dtype: string
  - name: response
    dtype: string
  splits:
  - name: train
    num_bytes: 6477736021
    num_examples: 4233915
  download_size: 4104476393
  dataset_size: 6477736021
---
<p><h1>🐋 OpenOrca-Chinese 数据集！🐋</h1></p>

感謝  [Open-Orca/OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca)  資料集的發布，為廣大NLP研究人員和開發者帶來了寶貴的資源！

這是一個對  [Open-Orca/OpenOrca](https://huggingface.co/datasets/Open-Orca/OpenOrca)  資料集中文翻譯的版本，翻譯引擎為 Google 翻譯，希望能為中文 LLM 研究做出一點點貢獻。

<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.

