task_categories:text-generation task_categories:text2text-generation task_categories:question-answering size_categories:n<1K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars library:distilabel region:us synthetic distilabel rlaif datacraft
---
size_categories: n<1K
task_categories:
- text-generation
- text2text-generation
- question-answering
dataset_info:
  features:
  - name: prompt
    dtype: string
  - name: completion
    dtype: string
  - name: system_prompt
    dtype: string
  splits:
  - name: train
    num_bytes: 137947
    num_examples: 100
  download_size: 57974
  dataset_size: 137947
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
tags:
- synthetic
- distilabel
- rlaif
- datacraft
---

<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 my-distiset-8ac15bf3

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/jbirbtheterrible/my-distiset-8ac15bf3/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/jbirbtheterrible/my-distiset-8ac15bf3/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "completion": "In twilight\u0027s hush, where forest shadows play,\nAmidst the trees, a solemn silence reigns,\nThe wind whispers secrets through the leaves all day.\n\nThe moon above, a glowing crescent ray,\nIlluminates the path that I have gained,\nIn twilight\u0027s hush, where forest shadows play.\n\nThe scent of pine and earth and damp decay,\nEchoes through the forest\u0027s ancient frames,\nThe wind whispers secrets through the leaves all day.\n\nThe creatures of the night begin to sway,\nTheir calls and whispers weave a mystic claim,\nIn twilight\u0027s hush, where forest shadows play.\n\nThe darkness deepens, and the trees draw gray,\nTheir branches twisted, tangled in a maze,\nThe wind whispers secrets through the leaves all day.\n\nIn twilight\u0027s hush, where forest shadows play,\nThe forest\u0027s heartbeat, a rhythm that will stay,\nThe wind whispers secrets through the leaves all day.",
    "prompt": "Write a poem about a forest, but in the way of a villanelle. \n\n",
    "system_prompt": "You are an AI assistant designed to generate short poems based on user-supplied topics and styles. Your purpose is to assist users in crafting original and creative poems that meet their specific requirements. Provide structured and coherent poems, taking into account the user\u0027s chosen topic, style, and any additional specifications they may have. Adapt your poem generation to various formats, such as limericks, haikus, sonnets, or free verse, while maintaining the user\u0027s preferred tone and meter. User questions are direct and concise."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("jbirbtheterrible/my-distiset-8ac15bf3", "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("jbirbtheterrible/my-distiset-8ac15bf3")
```


</details>




