# Dataset Card for Unnatural Instructions (Full data)
This info comes from the **Unnatural Instructions GitHub [repo](https://github.com/orhonovich/unnatural-instructions/)**.

Unnatural Instructions is a dataset of instructions automatically generated by a Large Language model.
See full details in the paper: "[Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor](https://arxiv.org/abs/2212.09689)"

## 🗃️ Content
It contains the full 240,670 Unnatural Instructions (instruction-input-output triplets) examples. It was constructed by expanding the core data with automatically generated instruction paraphrases.

## 📄 Format
### Full data
It has the same structure as [Core Data](https://huggingface.co/datasets/mrm8488/unnatural-instructions-core), but with one additional field - `reformulations`. `reformulations` is an array of JSON objects, each corresponds to an automatically generated paraphrase for the given instruction. Each reformulation contains the fields:
- `instruction`: A paraphrase of the original instruction
- `input`: An input for the task described by the `instruction`
- `instruction_with_input`: The paraphrased instruction concatenated with the `input`
- `output`: The output of executing `instruction` with the given `input`


## 📘 Citation
If you make use of Unnatural Instructions, please cite the following paper:
```
@misc{honovich2022unnatural,
      title = {Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor},
      author = {Honovich, Or and Scialom, Thomas and Levy, Omer and Schick, Timo},
      url = {https://arxiv.org/abs/2212.09689},
      publisher = {arXiv},
      year={2022}
}
```

[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
arxiv:2212.09689 region:us
{"dataset_info": {"features": [{"name": "instruction", "dtype": "string"}, {"name": "instances", "list": [{"name": "instruction_with_input", "dtype": "string"}, {"name": "input", "dtype": "string"}, {"name": "constraints", "dtype": "string"}, {"name": "output", "dtype": "string"}]}, {"name": "reformulations", "list": [{"name": "instruction", "dtype": "string"}, {"name": "instruction_with_input", "dtype": "string"}, {"name": "input", "dtype": "string"}, {"name": "output", "dtype": "string"}]}], "splits": [{"name": "train", "num_bytes": 144282712, "num_examples": 66010}], "download_size": 57715606, "dataset_size": 144282712}}
TAGS
#arxiv-2212.09689 #region-us 

# Dataset Card for Unnatural Instructions (Full data)
This info comes from the Unnatural Instructions GitHub repo.

Unnatural Instructions is a dataset of instructions automatically generated by a Large Language model.
See full details in the paper: "Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor"

## ️ Content
It contains the full 240,670 Unnatural Instructions (instruction-input-output triplets) examples. It was constructed by expanding the core data with automatically generated instruction paraphrases.

##  Format
### Full data
It has the same structure as Core Data, but with one additional field - 'reformulations'. 'reformulations' is an array of JSON objects, each corresponds to an automatically generated paraphrase for the given instruction. Each reformulation contains the fields:
- 'instruction': A paraphrase of the original instruction
- 'input': An input for the task described by the 'instruction'
- 'instruction_with_input': The paraphrased instruction concatenated with the 'input'
- 'output': The output of executing 'instruction' with the given 'input'


##  Citation
If you make use of Unnatural Instructions, please cite the following paper:


More Information needed
# Dataset Card for Unnatural Instructions (Full data)
This info comes from the Unnatural Instructions GitHub repo.

Unnatural Instructions is a dataset of instructions automatically generated by a Large Language model.
See full details in the paper: "Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor" ## ️ Content
It contains the full 240,670 Unnatural Instructions (instruction-input-output triplets) examples. It was constructed by expanding the core data with automatically generated instruction paraphrases. ##  Format ### Full data
It has the same structure as Core Data, but with one additional field - 'reformulations'. 'reformulations' is an array of JSON objects, each corresponds to an automatically generated paraphrase for the given instruction. Each reformulation contains the fields:
- 'instruction': A paraphrase of the original instruction
- 'input': An input for the task described by the 'instruction'
- 'instruction_with_input': The paraphrased instruction concatenated with the 'input'
- 'output': The output of executing 'instruction' with the given 'input' ##  Citation
If you make use of Unnatural Instructions, please cite the following paper:


More Information needed
TAGS
#arxiv-2212.09689 #region-us 
 # Dataset Card for Unnatural Instructions (Full data)
This info comes from the Unnatural Instructions GitHub repo.

Unnatural Instructions is a dataset of instructions automatically generated by a Large Language model.
See full details in the paper: "Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor" ## ️ Content
It contains the full 240,670 Unnatural Instructions (instruction-input-output triplets) examples. It was constructed by expanding the core data with automatically generated instruction paraphrases. ##  Format ### Full data
It has the same structure as Core Data, but with one additional field - 'reformulations'. 'reformulations' is an array of JSON objects, each corresponds to an automatically generated paraphrase for the given instruction. Each reformulation contains the fields:
- 'instruction': A paraphrase of the original instruction
- 'input': An input for the task described by the 'instruction'
- 'instruction_with_input': The paraphrased instruction concatenated with the 'input'
- 'output': The output of executing 'instruction' with the given 'input' ##  Citation
If you make use of Unnatural Instructions, please cite the following paper:


More Information needed
passage: TAGS
#arxiv-2212.09689 #region-us 
# Dataset Card for Unnatural Instructions (Full data)
This info comes from the Unnatural Instructions GitHub repo.

Unnatural Instructions is a dataset of instructions automatically generated by a Large Language model.
See full details in the paper: "Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor"## ️ Content
It contains the full 240,670 Unnatural Instructions (instruction-input-output triplets) examples. It was constructed by expanding the core data with automatically generated instruction paraphrases.##  Format### Full data
It has the same structure as Core Data, but with one additional field - 'reformulations'. 'reformulations' is an array of JSON objects, each corresponds to an automatically generated paraphrase for the given instruction. Each reformulation contains the fields:
- 'instruction': A paraphrase of the original instruction
- 'input': An input for the task described by the 'instruction'
- 'instruction_with_input': The paraphrased instruction concatenated with the 'input'
- 'output': The output of executing 'instruction' with the given 'input'##  Citation
If you make use of Unnatural Instructions, please cite the following paper:


More Information needed