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': positive
          '1': negative
          '2': neutral
  splits:
  - name: train
    num_bytes: 208058
    num_examples: 469
  download_size: 90475
  dataset_size: 208058
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-be899639

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/chaosIsRythmic/my-distiset-be899639/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/chaosIsRythmic/my-distiset-be899639/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "label": 2,
    "text": "The recent implementation of the personalized medicine approach in our institution has led to a substantial improvement in treatment efficacy, particularly in patients with metastatic breast cancer. However, the lack of standardization in biomarker testing protocols has resulted in inconsistent outcomes and added complexity to the treatment planning process. Furthermore, the high cost of next-generation sequencing technologies is a significant concern, as it may limit access to these life-saving therapies for underprivileged patients."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("chaosIsRythmic/my-distiset-be899639", "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("chaosIsRythmic/my-distiset-be899639")
```


</details>




