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: labels
    sequence:
      class_label:
        names:
          '0': valuable learning
          '1': excessive workload
          '2': unclear explanations
          '3': outdated content
          '4': lacking depth
          '5': approachable instructor
          '6': lacking resources
          '7': engaging material
          '8': comprehensive content
          '9': meaningful projects
          '10': unclear instructions
          '11': unhelpful instructor
          '12': helpful resources
          '13': passionate instructor
          '14': challenging assignments
          '15': disappointing experience
          '16': relevant to real-world
          '17': well-structured
          '18': improved understanding
          '19': clear explanations
  splits:
  - name: train
    num_bytes: 181650
    num_examples: 499
  download_size: 67614
  dataset_size: 181650
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 gen-ai-course-feedback

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/introtogenairize/gen-ai-course-feedback/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/introtogenairize/gen-ai-course-feedback/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "labels": [
        7,
        16,
        4,
        19
    ],
    "text": "While taking this Generative AI course, I found that the instructor provided excellent explanations of complex concepts, and the assignments were engaging and relevant to the topic. However, I felt that the course material could have delved deeper into the applications of Generative AI in real-world scenarios."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("introtogenairize/gen-ai-course-feedback", "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("introtogenairize/gen-ai-course-feedback")
```


</details>




