distilabel-internal-testing/test-dockerfile

---
size_categories: n<1K
dataset_info:
features:
- name: instruction
dtype: string
- name: generation_model
dtype: string
- name: generation
dtype: string
splits:
- name: train
num_bytes: 192
num_examples: 1
download_size: 2877
dataset_size: 192
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
tags:
- synthetic
- distilabel
- rlaif
---

<p align="left">
<a href="https://github.com/argilla-io/distilabel">
<img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
</a>
</p>

# Dataset Card for test-dockerfile

This dataset has been created with [distilabel](https://distilabel.argilla.io/).

## Dataset Summary

This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI:

```console
distilabel pipeline run --config "https://huggingface.co/datasets/distilabel-internal-testing/test-dockerfile/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/distilabel-internal-testing/test-dockerfile/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:

<details><summary> Configuration: default </summary><hr>

```json
{
"generation": "\n\nA priest, a rabbi and a minister walk into a bar... ...and the bartender says \"What is this? A joke?\"",
"generation_model": "/Users/ignacio/Downloads/openhermes-2.5-mistral-7b.Q4_K_M.gguf",
"instruction": "Tell me a joke."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("distilabel-internal-testing/test-dockerfile", "default")
```

Or simply as it follows, since there's only one configuration and is named `default`:

```python
from datasets import load_dataset

ds = load_dataset("distilabel-internal-testing/test-dockerfile")
```

</details>