---
dataset_info:
  features:
  - name: instruction
    dtype: string
  - name: input
    dtype: string
  - name: output
    dtype: string
  splits:
  - name: train
    num_bytes: 5235566
    num_examples: 40639
  - name: test
    num_bytes: 57761
    num_examples: 300
  download_size: 2474695
  dataset_size: 5293327
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
license: mit
tags:
- nl2bash
- shell
- instruction
- code
pretty_name: NL2SH-alpaca-format
size_categories:
- 10K<n<100K
---

# NL2SH-ALPACA (Alpaca-style)

This is a **reformatted version of the NL2SH-ALFA dataset** originally created by [westenfelder/NL2SH-ALFA](https://huggingface.co/datasets/westenfelder/NL2SH-ALFA).  

It has been **converted to Alpaca-style format and prepared for instruction fine-tuning** by **Anshuman Jena**, who acted as the **converter and maintainer** of this version.

```json
{
  "instruction": "<natural language instruction>",
  "input": "",
  "output": "<bash command>"
}
```
Additionally, for the **test split**, the original `bash2` (alternative command) and `difficulty` fields have been **included in the output**.

This dataset can be used to train instruction-following models for translating **natural language instructions to shell commands**.

---
### Data Fields

The data fields are as follows:

* `instruction`: natural language description of the shell task the model should perform. Each instruction is unique.
* `input`: optional context or input for the task. In this dataset, this field is empty for all examples.
* `output`: the shell command corresponding to the instruction. For the **test split**, alternative commands (`bash2`) and difficulty are appended to the output.

---
### Data Instances

An example of "train" looks as follows:

```json
{
    'instruction': 'Compile C code and cache compiled output (to use `ccache` on all `gcc` invocations, see the note above)',
    'input': '',
    'output': 'ccache gcc path/to/file.c'
}
```

---
### Data Splits

|              |  train | test |
| ------------ | -----: | ---: |
| NL2SH-ALPACA | 40,639 |  300 |

---
### How to load

```python
from datasets import load_dataset
ds = load_dataset("abandonedmonk/NL2SH-ALPACA")
print(ds["train"][0])
```

---
### Citation

If you use this dataset, please cite the original work:

```
@misc{westenfelder2025nl2sh,
title={NL2SH-ALFA},
author={westenfelder},
year={2025},
howpublished={\url{[https://huggingface.co/datasets/westenfelder/NL2SH-ALFA}}](https://huggingface.co/datasets/westenfelder/NL2SH-ALFA}})
}

```

This version of the dataset was **converted to Alpaca-style format and maintained by Anshuman Jena**.