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awesome-instruction-tunning-datasets Awesome

A collection of AWESOME datasets for instruction tuning.

There is a trend of improving LLM (large language models) by fine-tuning with instructions. As data-centric AI is becoming more and more popular, we need better quality datasets to train our models. This repository is a collection of datasets for instruction tuning.

Note that dataset generated by calling OpenAI API cannot be used to develop models that compete with OpenAI due to OpenAI's terms of use 2(c)(iii).

An awesome list of foundation models can be found here.

Datasets

  • Alpaca Dataset

    Size: 52K (English)
    Source: self-instruct from 175 seed instructions by OpenAI API
    Cost: less than US$ 500
    License: CC By NC 4.0; OpenAI terms of use
  • InstructionWild

    Size: 104K (English, Chinese)
    Source: self-instruct from 429 seed instructions collected from the Internet
    Cost: US$ 880
    License: Research only; OpenAI terms of use
  • Guanaco Dataset

    Self-instruct dataset

    Size: 98K (English, Simplified Chinese, Traditional Chinese HK & TW, Janpanese)
    Source: self-instruct from 175 translated seed instructions of Alpaca Dataset
    Cost: US$ 6K
    License: GPL-3.0; OpenAI terms of use

    Chat dataset

    Size: 49K

    Close-QA: give a passage and a question, generate the answer.

    Size: 99K

    Close-Question: give a passage, raise proper questions.

    Size: 107K
  • BELLE

    Self-instruct dataset

    Size: 1.5M (Chinese)
    Source: self-instruct from 175 translated seed instructions of Alpaca Dataset
    License: Research only; OpenAI terms of use

    Math dataset

    Size: 250K (Chinese)

    Multi-turn chat dataset

    Size: 800K (Chinese)
  • Alpaca-CoT Dataset

    Size: 75K
    Source: FLAN Chain-of-Thought dataset
  • OIG-43M Dataset [preprocess]

    Size: 43M
    Source: Collected by Together, LAION, and Ontocord.ai.
  • GPT4All Dataset

    Size: 806K
    Source: filtered from subset of LAION OIG, StackOverflow Question, BigSciense/p3 dataset. Answered by OpenAI API.
  • Camel Dataset

    Chat dataset

    Size: 107K
    Source: role-playing between AIs (Open AI API)
  • Vicuna Dataset

    Size: 75K (Unavailable due to privacy concern)
    Source: ShareGPT

Derivative Datasets

  • Cabrita Dataset

    Size: 52K (Portuguese)
    Source: translated from Alpaca Data
    Cost: US$ 8
    License: CC By NC 4.0; OpenAI terms of use
  • Japanese Alpaca Dataset

    Size: 52K (Japanese)
    Source: translated from Alpaca Data by ChatGPT API.
    Cost: US$ 45
    License: CC By NC 4.0; OpenAI terms of use
  • Chinese Alpaca Dataset

    Size: 52K (Chinese)
    Source: translated from Alpaca Data by ChatGPT API.
    Cost: US$ 30-45
    License: CC By NC 4.0; OpenAI terms of use
  • Alpaca Chinese Dataset

    Size: 52K (Chinese)
    Source: translated from Alpaca Data by ChatGPT API.
    Cost: Volunteer
    License: CC By NC 4.0; OpenAI terms of use

Dataset used in InstructGPT

InstructGPT

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