Datasets:
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---
size_categories: n<1K
task_categories:
- text-classification
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': data-science-ai-ml
'1': personal-development
'2': energy-sector
'3': finance
'4': business
'5': development
splits:
- name: train
num_bytes: 3539
num_examples: 12
download_size: 5558
dataset_size: 3539
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-ce202f9a
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/hjerpe/my-distiset-ce202f9a/raw/main/pipeline.yaml"
```
or explore the configuration:
```console
distilabel pipeline info --config "https://huggingface.co/datasets/hjerpe/my-distiset-ce202f9a/raw/main/pipeline.yaml"
```
## Dataset structure
The examples have the following structure per configuration:
<details><summary> Configuration: default </summary><hr>
```json
{
"label": 1,
"text": "As I reflect on the past year, I\u0027ve come to realize that my growth as an individual has been hindered by my tendency to procrastinate and lack of self-discipline. I\u0027ve been trying to establish a daily routine that includes time for meditation, reading, and exercise, but I often find myself getting distracted by social media and television. I\u0027m hoping to break free from these habits and develop a stronger sense of purpose and direction in life."
}
```
This subset can be loaded as:
```python
from datasets import load_dataset
ds = load_dataset("hjerpe/my-distiset-ce202f9a", "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("hjerpe/my-distiset-ce202f9a")
```
</details>
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