README.md

---
language:
- nb
size_categories: n<1K
dataset_info:
  features:
  - name: _id
    dtype: string
  - name: url
    dtype: string
  - name: title
    dtype: string
  - name: text
    dtype: string
  - name: score
    dtype: float64
  - name: views
    dtype: float64
  - name: model_name
    dtype: string
  - name: query
    dtype: string
  splits:
  - name: train
    num_bytes: 820541
    num_examples: 1500
  download_size: 534948
  dataset_size: 820541
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 cohere-wikipedia-2023-11-no-queries

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/rasdani/cohere-wikipedia-2023-11-no-queries/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/rasdani/cohere-wikipedia-2023-11-no-queries/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "_id": "20231101.no_262035_4",
    "model_name": "gpt-4o",
    "query": "Hva er eksekutivfunksjoner i nevropsykologi?",
    "score": 1.0,
    "text": "Evne til \u00e5 strukturere, planlegge, igangsette og kontrollere sammensatte handlinger (eksekutivfunksjoner).",
    "title": "Nevropsykologi",
    "url": "https://no.wikipedia.org/wiki/Nevropsykologi",
    "views": 728.6967671316081
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("rasdani/cohere-wikipedia-2023-11-no-queries", "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("rasdani/cohere-wikipedia-2023-11-no-queries")
```


</details>