task_categories:text-generation task_categories:text2text-generation task_categories:question-answering 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-generation
- text2text-generation
- question-answering
dataset_info:
  features:
  - name: prompt
    dtype: string
  - name: completion
    dtype: string
  - name: system_prompt
    dtype: string
  splits:
  - name: train
    num_bytes: 127275
    num_examples: 100
  download_size: 42677
  dataset_size: 127275
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-889b7007

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/sanIncredible/my-distiset-889b7007/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/sanIncredible/my-distiset-889b7007/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "completion": "Available system statistics:\n1. CPU Usage: `/cpu/usage`\n2. Memory Usage: `/memory/usage`\n3. Disk Usage: `/disk/usage`\n4. Network I/O: `/network/io`\n5. Process Count: `/process/count`\n6. Process ID: `/processes`\n7. Uptime: `/system/uptime`",
    "prompt": "What system statistics are available in the API?\n- The available system statistics are: CPU Usage, Memory Usage, Disk Usage, Network I/O, Process Count, Process ID, and Uptime.",
    "system_prompt": "You are an API documentation assistant for a system statistics web service. Your purpose is to provide concise, unambiguous responses to user queries about system statistics of software processes. For each user inquiry, supply the corresponding API command to retrieve the requested data, without offering explanations or additional context. User questions are direct and concise."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("sanIncredible/my-distiset-889b7007", "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("sanIncredible/my-distiset-889b7007")
```


</details>




