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
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': reference
          '1': error-log
          '2': tutorial
          '3': release-note
  splits:
  - name: train
    num_bytes: 2733
    num_examples: 10
  download_size: 4082
  dataset_size: 2733
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 OpenRouter-api

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/kakumusic/OpenRouter-api/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/kakumusic/OpenRouter-api/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "label": 3,
    "text": "With this release, we are introducing a novel optimization technique for our OpenRouter.ai service, which significantly improves the performance of our path computation elements in scenarios with high network churn. This enhancement is particularly relevant for customers who operate in environments with frequent topology changes."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("kakumusic/OpenRouter-api", "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("kakumusic/OpenRouter-api")
```


</details>




