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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 intent-classification
+
+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/Dev523/intent-classification/raw/main/pipeline.yaml"
+```
+
+or explore the configuration:
+
+```console
+distilabel pipeline info --config "https://huggingface.co/datasets/Dev523/intent-classification/raw/main/pipeline.yaml"
+```
+
+## Dataset structure
+
+The examples have the following structure per configuration:
+
+
+<details><summary> Configuration: default </summary><hr>
+
+```json
+{
+    "labels": [
+        1,
+        3
+    ],
+    "text": "I recently purchased a product from your company, but it didn\u0027t meet my expectations. The material was flimsy and the design was not as sleek as I thought it would be."
+}
+```
+
+This subset can be loaded as:
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("Dev523/intent-classification", "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("Dev523/intent-classification")
+```
+
+
+</details>
+
+
+
+