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README.md

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 ---
+size_categories: n<1K
 dataset_info:
   features:
   - name: text
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   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-64eab852
+
+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/apol/my-distiset-64eab852/raw/main/pipeline.yaml"
+```
+
+or explore the configuration:
+
+```console
+distilabel pipeline info --config "https://huggingface.co/datasets/apol/my-distiset-64eab852/raw/main/pipeline.yaml"
+```
+
+## Dataset structure
+
+The examples have the following structure per configuration:
+
+
+<details><summary> Configuration: default </summary><hr>
+
+```json
+{
+    "label": 3,
+    "text": "This sleek and luxurious Italian leather backpack features an intricate gold buckle and premium stitching, perfect for carrying your laptop, tablet, and other essentials to and from work or travel."
+}
+```
+
+This subset can be loaded as:
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("apol/my-distiset-64eab852", "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("apol/my-distiset-64eab852")
+```
+
+
+</details>
+
+
+
+