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: 194353
    num_examples: 100
  download_size: 108229
  dataset_size: 194353
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-cyberss

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-cyberss/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/hackulos/my-distiset-87bfa762-cyberss/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 Parliament and the Council of the European Union, in accordance with international standards, have established regulations to ensure the cybersecurity of digital products and services in the Arctic region, amending existing regulations and directives to strengthen security measures for polar expeditions.",
    "negative_retrieval": "REGULATION (EU) 2024/2847 OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL\n\nof 23 October 2024\n\non horizontal efficiency requirements for automotive products with digital elements and amending Regulations (EU) No 168/2013 and (EU) No 2019/1020 and Directive (EU) 2020/1828\n\n(Text with EEA relevance)\n\nThe European Parliament and the Council of the European Union adopted this regulation to enhance the overall efficiency of automotive products.",
    "positive_reranking": "The European Parliament and the Council of the European Union, in accordance with international guidelines, have established regulations to ensure the cybersecurity of digital products and services, amending existing regulations and directives to strengthen security measures.",
    "positive_retrieval": "Can you provide more information about the recent European Parliament and Council regulation of the L series?",
    "question": "Can you provide more information about the recent European Parliament and Council regulation of the L series?",
    "response": "Based on the provided document, the recent European Parliament and Council regulation is actually part of the \"L series\" but it is actually labeled as \"2024/2847\". \n\nHowever, the document does not provide more information about the \"L series\" itself. It appears to be a label or a series number for EU regulations, but it does not contain any additional details.\n\nThe regulation itself, labeled as \"2024/2847\", is about horizontal cybersecurity requirements for products with digital elements and amending existing regulations and directives related to cybersecurity."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

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


</details>




