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
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: prompt
    dtype: string
  - name: completion
    dtype: string
  - name: meta
    struct:
    - name: category
      dtype: string
    - name: completion
      dtype: string
    - name: id
      dtype: int64
    - name: input
      dtype: string
    - name: motivation_app
      dtype: string
    - name: prompt
      dtype: string
    - name: source
      dtype: string
    - name: subcategory
      dtype: string
  - name: merged_generation
    sequence: string
  splits:
  - name: train
    num_bytes: 456140
    num_examples: 327
  download_size: 292213
  dataset_size: 456140
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 first-distiset-with-routed-batches-new

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/first-distiset-with-routed-batches-new/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/distilabel-internal-testing/first-distiset-with-routed-batches-new/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "completion": "h\u01ceo",
    "merged_generation": [
        "I slept for 1 seconds",
        "I slept for 1 seconds",
        "I slept for 1 seconds"
    ],
    "meta": {
        "category": null,
        "completion": "h\u01ceo",
        "id": 125,
        "input": "\u597d",
        "motivation_app": "Doulingo",
        "prompt": "What sound does this make?\n Input: \u597d",
        "source": "self-instruct",
        "subcategory": null
    },
    "prompt": "What sound does this make?\n Input: \u597d"
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("distilabel-internal-testing/first-distiset-with-routed-batches-new", "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/first-distiset-with-routed-batches-new")
```


</details>
