---
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: statistics_text_generation_0
      struct:
      - name: input_tokens
        dtype: int64
      - name: output_tokens
        dtype: int64
  - name: model_name
    dtype: string
  splits:
  - name: train
    num_bytes: 17686
    num_examples: 10
  download_size: 22060
  dataset_size: 17686
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

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/vinaybabu/distilabel-example/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/vinaybabu/distilabel-example/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": "Arianna has 12 chocolates more than Danny. Danny has 6 chocolates more than Robbie. Arianna has twice as many chocolates as Robbie has. How many chocolates does Danny have?",
                "role": "user"
            }
        ],
        "raw_output_text_generation_0": "Let the number of chocolates Robbie has be \\( r \\).\n\nFrom the problem, we know:\n\n1. Danny has 6 chocolates more than Robbie:\n   \\[\n   d = r + 6\n   \\]\n\n2. Arianna has 12 chocolates more than Danny:\n   \\[\n   a = d + 12\n   \\]\n\n3. Arianna has twice as many chocolates as Robbie:\n   \\[\n   a = 2r\n   \\]\n\nWe can now substitute \\( d \\) into the equation for \\( a \\):\n\\[\na = (r + 6) + 12\n\\]\nThis",
        "statistics_text_generation_0": {
            "input_tokens": 45,
            "output_tokens": 128
        }
    },
    "generation": "Let the number of chocolates Robbie has be \\( r \\).\n\nFrom the problem, we know:\n\n1. Danny has 6 chocolates more than Robbie:\n   \\[\n   d = r + 6\n   \\]\n\n2. Arianna has 12 chocolates more than Danny:\n   \\[\n   a = d + 12\n   \\]\n\n3. Arianna has twice as many chocolates as Robbie:\n   \\[\n   a = 2r\n   \\]\n\nWe can now substitute \\( d \\) into the equation for \\( a \\):\n\\[\na = (r + 6) + 12\n\\]\nThis",
    "instruction": "Arianna has 12 chocolates more than Danny. Danny has 6 chocolates more than Robbie. Arianna has twice as many chocolates as Robbie has. How many chocolates does Danny have?",
    "model_name": "gpt-4o-mini"
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

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


</details>