size_categories:1K<n<10K format:parquet modality:tabular modality:text library:datasets library:pandas library:mlcroissant library:polars library:distilabel region:us synthetic distilabel rlaif
---
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: 1302295
    num_examples: 1500
  download_size: 648337
  dataset_size: 1302295
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-fa-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-fa-queries/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/rasdani/cohere-wikipedia-2023-11-fa-queries/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "_id": "20231101.fa_7766_23",
    "model_name": "gpt-4o",
    "query": "\u0686\u0631\u0627 \u0631\u0648\u0633\u200c\u0647\u0627 \u0627\u0632 \u062a\u0628\u0631\u06cc\u0632 \u062e\u0627\u0631\u062c \u0646\u0634\u062f\u0646\u062f\u061f",
    "score": 1.0,
    "text": "\u0645\u062e\u0628\u0631\u0627\u0644\u0633\u0644\u0637\u0646\u0647 \u0627\u0632 \u0647\u0645\u0627\u0646 \u0644\u062d\u0638\u0647 \u0648\u0631\u0648\u062f \u0628\u0647 \u062a\u0628\u0631\u06cc\u0632 \u0628\u0627 \u06cc\u06a9 \u0645\u0634\u06a9\u0644 \u062c\u062f\u06cc \u0631\u0648\u0628\u0631\u0648 \u0634\u062f\u061b \u0631\u0648\u0633\u200c\u0647\u0627 \u0628\u0647 \u0628\u0647\u0627\u0646\u0647 \u062d\u0645\u0627\u06cc\u062a \u0627\u0632 \u0628\u0648\u0631\u0698\u0648\u0627\u0632\u06cc \u0635\u0646\u0639\u062a\u06cc \u0648 \u062a\u062c\u0627\u0631\u06cc \u062a\u0628\u0631\u06cc\u0632 \u0648 \u0628\u0631\u0642\u0631\u0627\u0631\u06cc \u0646\u0638\u0645 \u0648 \u0627\u0645\u0646\u06cc\u062a\u060c \u0642\u0648\u0627\u06cc \u0646\u0638\u0627\u0645\u06cc \u062e\u0648\u062f \u0631\u0627 \u062f\u0631 \u0634\u0647\u0631 \u0645\u0633\u062a\u0642\u0631 \u06a9\u0631\u062f\u0647 \u0628\u0648\u062f\u0646\u062f. \u0627\u0633\u062a\u0627\u0646\u062f\u0627\u0631 \u0645\u0634\u0631\u0648\u0637\u0647\u200c\u062e\u0648\u0627\u0647 \u0627\u0632 \u0631\u0648\u0633\u200c\u0647\u0627 \u062e\u0648\u0627\u0633\u062a \u062d\u0627\u0644\u0627 \u06a9\u0647 \u062a\u0647\u0631\u0627\u0646 \u0628\u0647 \u062f\u0633\u062a \u0645\u0634\u0631\u0648\u0637\u0647\u200c\u062e\u0648\u0627\u0647\u0627\u0646 \u0627\u0641\u062a\u0627\u062f\u0647 \u0648 \u0627\u062f\u0627\u0631\u0647 \u0645\u0645\u0644\u06a9\u062a \u0628\u0631\u0627\u0633\u0627\u0633 \u0642\u0627\u0646\u0648\u0646 \u0627\u0633\u062a\u0648\u0627\u0631 \u0634\u062f\u0647\u060c \u0644\u0632\u0648\u0645\u06cc \u0628\u0647 \u062d\u0636\u0648\u0631 \u0631\u0648\u0633\u200c\u0647\u0627 \u0646\u06cc\u0633\u062a \u0648 \u0628\u0627\u06cc\u062f \u0642\u0648\u0627\u06cc \u0646\u0638\u0627\u0645\u06cc \u0631\u0648\u0633 \u0627\u0632 \u062a\u0628\u0631\u06cc\u0632 \u062e\u0627\u0631\u062c \u0634\u0648\u0646\u062f. \u0631\u0648\u0633\u200c\u0647\u0627 \u0627\u063a\u062a\u0634\u0627\u0634 \u0648 \u0646\u0627 \u0627\u0645\u0646\u06cc \u0634\u0647\u0631 \u0631\u0627 \u0645\u062e\u0644 \u0627\u0645\u0646\u06cc\u062a \u062a\u0627\u062c\u0631\u0627\u0646 \u062f\u0648 \u062a\u0627\u0628\u0639\u06cc\u062a\u06cc \u062a\u0628\u0631\u06cc\u0632 \u0645\u06cc\u200c\u062f\u0627\u0646\u0633\u062a\u0646\u062f \u0648 \u062d\u0636\u0648\u0631 \u0627\u0641\u0631\u0627\u062f \u0645\u0633\u0644\u062d \u063a\u06cc\u0631\u062f\u0648\u0644\u062a\u06cc \u0627\u0632 \u062c\u0645\u0644\u0647 \u0633\u062a\u0627\u0631\u062e\u0627\u0646 \u0648 \u0628\u0627\u0642\u0631\u062e\u0627\u0646 \u0631\u0627 \u0628\u0647\u0627\u0646\u0647 \u06a9\u0631\u062f\u0647 \u0648 \u0628\u0647 \u062f\u0631\u062e\u0648\u0627\u0633\u062a \u062f\u0648\u0644\u062a \u0645\u0634\u0631\u0648\u0637\u0647 \u0627\u06cc\u0631\u0627\u0646 \u067e\u0627\u0633\u062e \u0645\u062b\u0628\u062a \u0646\u062f\u0627\u062f\u0646\u062f.",
    "title": "\u0633\u062a\u0627\u0631\u062e\u0627\u0646",
    "url": "https://fa.wikipedia.org/wiki/%D8%B3%D8%AA%D8%A7%D8%B1%D8%AE%D8%A7%D9%86",
    "views": 8794.55436178889
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("rasdani/cohere-wikipedia-2023-11-fa-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-fa-queries")
```


</details>
