language:en size_categories:n<1K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars library:distilabel doi:10.57967/hf/4182 region:us synthetic distilabel rlaif datacraft
---
language:
- en
size_categories: n<1K
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': cloud-computing
          '1': creative-design
          '2': digital-marketing
          '3': financial-management
          '4': communications
          '5': user-experience-design
          '6': mobile-app-development
          '7': web-development
          '8': system-administration
          '9': network-administration
          '10': team-management
          '11': financial-analysis
          '12': project-management
          '13': data-visualization
          '14': cyber-security
          '15': network-engineering
          '16': business-analysis
          '17': database-management
          '18': software-engineering
          '19': data-science
          '20': machine-learning
          '21': artificial-intelligence
  splits:
  - name: train
    num_bytes: 156930
    num_examples: 486
  download_size: 81549
  dataset_size: 156930
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 ideator

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/zhreyu/ideator/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/zhreyu/ideator/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "label": 17,
    "text": "The project aims to develop a novel stochastic control framework for dynamic risk management in complex financial networks, incorporating game-theoretic principles and machine learning algorithms to optimize portfolio allocation and minimize potential losses."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("zhreyu/ideator", "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("zhreyu/ideator")
```


</details>




