README.md

---
size_categories: n<1K
task_categories:
- text-generation
- text2text-generation
- text-retrieval
- question-answering
dataset_info:
  features:
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: response
    dtype: string
  splits:
  - name: train
    num_bytes: 12762
    num_examples: 18
  download_size: 7057
  dataset_size: 12762
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 Hactal_Repo

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/samuelsuen/Hactal_Repo/raw/main/pipeline.yaml"
```

or explore the configuration:

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

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "context": "Hong Kong Air Cargo Terminals Limited (Chinese: \u9999\u6e2f\u7a7a\u904b\u8ca8\u7ad9\u6709\u9650\u516c\u53f8), commonly known as Hactl, is one of the leading air cargo terminal operators in the world. Located at Hong Kong International Airport, it handled a total throughput of 1.65 million tonnes of cargo in 2018.",
    "question": null,
    "response": "The document does not mention anything about Hong Kong Air Cargo Terminals Limited (Hactl) handling a specific amount of cargo in 2018. It only mentions that it is one of the leading air cargo terminal operators in the world, but provides no further details on its throughput or any other metrics."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("samuelsuen/Hactal_Repo", "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("samuelsuen/Hactal_Repo")
```


</details>