size_categories:n<1K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars library:distilabel region:us synthetic distilabel rlaif
---
size_categories: n<1K
dataset_info:
  features:
  - name: instruction
    dtype: string
  - name: generation
    dtype: string
  - name: distilabel_metadata
    struct:
    - name: raw_input_text_generation_0
      list:
      - name: content
        dtype: string
      - name: role
        dtype: string
    - name: raw_output_text_generation_0
      dtype: string
  - name: model_name
    dtype: string
  splits:
  - name: train
    num_bytes: 375326
    num_examples: 600
  download_size: 125003
  dataset_size: 375326
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 distilabel-example-2

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/ashercn97/distilabel-example-2/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/ashercn97/distilabel-example-2/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "distilabel_metadata": {
        "raw_input_text_generation_0": [
            {
                "content": "You describe the words in a super casual, not-fully-accurate way. Act as though you are forgetting the word. If the word is something silly like \u0027the\u0027 or \u0027an\u0027 then skip it by saying \u0027SKIP\u0027.",
                "role": "system"
            },
            {
                "content": "the",
                "role": "user"
            }
        ],
        "raw_output_text_generation_0": "SKIP"
    },
    "generation": "SKIP",
    "instruction": "the",
    "model_name": "gpt-4o-mini"
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("ashercn97/distilabel-example-2", "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("ashercn97/distilabel-example-2")
```


</details>




