size_categories:1K<n<10K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars library:distilabel region:us synthetic distilabel rlaif datacraft
---
size_categories: 1K<n<10K
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': hfr-etiologies
          '1': vte-risk-factor
          '2': hf-ef-mechanism
          '3': other-diagnosis
          '4': hf-diagnosis
          '5': comorbidity
          '6': ef-mechanism
          '7': urgent-condition
          '8': cardiomyopathy-diagnosis
          '9': atrial-fibrillation
          '10': chf-diagnosis
  splits:
  - name: train
    num_bytes: 513322
    num_examples: 1000
  download_size: 177697
  dataset_size: 513322
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-cf870b56

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/grq79/my-distiset-cf870b56/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/grq79/my-distiset-cf870b56/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "label": 9,
    "text": "The patient\u0027s electrocardiogram revealed a rapid and irregular heart rhythm, characterized by disorganized atrial depolarizations and a lack of P waves. The presence of atrial fibrillation was further confirmed by the patient\u0027s symptoms of palpitations, shortness of breath, and fatigue. The treating cardiologist has prescribed anticoagulation therapy to prevent thromboembolic complications and rate control medications to alleviate symptoms. The patient\u0027s condition is consistent with the diagnostic criteria for atrial fibrillation, as outlined in the 2022 ACC/AHA/HRS guideline for the management of atrial fibrillation."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("grq79/my-distiset-cf870b56", "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("grq79/my-distiset-cf870b56")
```


</details>




