task_categories:text-generation task_categories:text2text-generation task_categories:text-retrieval task_categories:question-answering task_categories:sentence-similarity 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
- text-retrieval
- question-answering
- sentence-similarity
dataset_info:
  features:
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: response
    dtype: string
  - name: positive_retrieval
    dtype: string
  - name: negative_retrieval
    dtype: string
  - name: positive_reranking
    dtype: string
  - name: negative_reranking
    dtype: string
  splits:
  - name: train
    num_bytes: 195028
    num_examples: 100
  download_size: 106647
  dataset_size: 195028
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-87bfa762-cybers

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/hackulos/my-distiset-87bfa762-cybers/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/hackulos/my-distiset-87bfa762-cybers/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "context": "of the European Union L series\n\n2024/2847 20.11.2024\n\nREGULATION (EU) 2024/2847 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL\n\nof 23 October 2024\n\non horizontal cybersecurity requirements for products with digital elements and amending Regulations (EU) No 168/2013 and (EU) No 2019/1020 and Directive (EU) 2020/1828 (Cyber Resilience Act)\n\n(Text with EEA relevance)\n\nTHE EUROPEAN PARLIAMENT AND THE COUNCIL OF THE EUROPEAN UNION,",
    "negative_reranking": "The European Union has established a regulation that sets out cybersecurity requirements for products with digital elements and amends existing regulations, including those related to Directive (EU) 2019/444, to enhance digitalization in the automotive sector.",
    "negative_retrieval": "The European Parliament and Council of the European Union established Regulation (EU) 2024/2847 of 23 October 2024 on horizontal requirements for EU digital product passports to safeguard national cybersecurity standards.",
    "positive_reranking": "The European Union has established a regulation that sets out cybersecurity requirements for products with digital components and amends existing regulations, including those related to Directive (EU) 2020/1828.",
    "positive_retrieval": "What is the EU regulation (EU) 2024/2847 of the European Parliament and of the Council of 23 October 2024 on horizontal cybersecurity requirements for digital products and their amendments?",
    "question": "What is the EU regulation (EU) 2024/2847 of the European Parliament and of the Council of 23 October 2024 on horizontal cybersecurity requirements for digital products and their amendments?",
    "response": "The EU regulation (EU) 2024/2847 of the European Parliament and of the Council of 23 October 2024 is on horizontal cybersecurity requirements for products with digital elements and amending Regulations (EU) No 168/2019 and (EU) No 2019/1020 and Directive (EU) 2020/1828 (Cyber Resilience Act)."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("hackulos/my-distiset-87bfa762-cybers", "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("hackulos/my-distiset-87bfa762-cybers")
```


</details>




