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': 正面評論
          '1': 負面評論
  splits:
  - name: train
    num_bytes: 2875
    num_examples: 10
  download_size: 4433
  dataset_size: 2875
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-3bfc714e

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/chinfung/my-distiset-3bfc714e/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/chinfung/my-distiset-3bfc714e/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "label": 0,
    "text": "I just watched \u0027The Shawshank Redemption\u0027 and was thoroughly impressed by the director\u0027s ability to balance drama and hope in the face of adversity. The performances by Morgan Freeman and Tim Robbins were outstanding, bringing depth and nuance to their characters. The story is well-written and engaging, with a narrative that keeps you on the edge of your seat. While some may find the pacing a bit slow, I believe it\u0027s a minor quibble in an otherwise masterful film."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("chinfung/my-distiset-3bfc714e", "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("chinfung/my-distiset-3bfc714e")
```


</details>




