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': persönlich
          '1': e-mail
          '2': interne-mitteilung
          '3': technischer-bericht
          '4': protokoll
          '5': marketingmaterial
          '6': wichtig
          '7': ausarbeit
          '8': auftrag
          '9': kundenbeschwerde
          '10': geschäftsbrief
          '11': information
          '12': behörden
          '13': pressemitteilung
          '14': projektplan
          '15': amt
          '16': vertrag
          '17': rechnung
  splits:
  - name: train
    num_bytes: 4108
    num_examples: 10
  download_size: 6199
  dataset_size: 4108
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 DatensatzTextErkennung

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/Cyberz/DatensatzTextErkennung/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/Cyberz/DatensatzTextErkennung/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "label": 10,
    "text": "Dear Sir/Madam, I am writing to inform you that the delivery of goods has been postponed due to unforeseen circumstances. The new estimated date of delivery is now set for the 15th of next month. Please note that we will provide an updated delivery schedule in due course. Thank you for your understanding and cooperation."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("Cyberz/DatensatzTextErkennung", "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("Cyberz/DatensatzTextErkennung")
```


</details>




