task_categories:text-classification 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
task_categories:
- text-classification
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': low-risk
          '1': high-risk
          '2': stable
          '3': critical
  splits:
  - name: train
    num_bytes: 2352
    num_examples: 10
  download_size: 3598
  dataset_size: 2352
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 my-distiset-686a2cf2

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/Shubham2230/my-distiset-686a2cf2/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/Shubham2230/my-distiset-686a2cf2/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "label": 0,
    "text": "The patient, Jane Doe, a 35-year-old woman, has been experiencing recurring headaches and dizziness after taking her prescribed medication. Her doctor has ordered further tests to rule out any potential side effects and advises her to follow a strict diet to alleviate symptoms. In the meantime, she is advised to rest and avoid strenuous activities."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("Shubham2230/my-distiset-686a2cf2", "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("Shubham2230/my-distiset-686a2cf2")
```


</details>




