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
  splits:
  - name: train
    num_bytes: 22232
    num_examples: 10
  download_size: 21962
  dataset_size: 22232
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-ba327a12

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/zomd/my-distiset-ba327a12/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/zomd/my-distiset-ba327a12/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "completion": "AI Server\uc5d0 \ub85c\uadf8 \ud30c\uc77c\uc744 \ud655\uc778\ud558\ub294 \ubc29\ubc95\uc740 \uc5ec\ub7ec \uac00\uc9c0\uac00 \uc788\uc2b5\ub2c8\ub2e4. \uc77c\ubc18\uc801\uc73c\ub85c AI Server\ub294 \ub85c\uadf8 \ud30c\uc77c\uc744 \ub0a8\uaca8\ub450\ub294 \uc704\uce58\uc5d0 \ub530\ub77c \ub2e4\ub974\uba70, \uadf8 \uc704\uce58\uac00 \uc5ec\ub7ec \uacf3\uc5d0 \ubd84\uc0b0\ub418\uc5b4 \uc788\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc544\ub798\ub294 AI Server\uc5d0 \ub85c\uadf8 \ud30c\uc77c\uc744 \ud655\uc778\ud558\ub294 \uc77c\ubc18\uc801\uc778 \ubc29\ubc95\ub4e4\uc785\ub2c8\ub2e4.\n\n1. **\uc6b4\uc601 \uccb4\uc81c\uc758 \ub85c\uadf8 \ud30c\uc77c \uacbd\ub85c**: \uc6b4\uc601 \uccb4\uc81c\ubcc4\ub85c \ub85c\uadf8 \ud30c\uc77c\uc774 \uc800\uc7a5\ub418\ub294 \uacbd\ub85c\uac00 \ub2e4\ub985\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, Windows\ub294 \ub2e4\uc74c\uacfc \uac19\uc740 \uacbd\ub85c\uc5d0 \ub85c\uadf8 \ud30c\uc77c\uc744 \uc800\uc7a5\ud569\ub2c8\ub2e4.\n * `C:\\Windows\\System32\\LogFiles`\n * `C:\\Users\\\u003c\uc720\uc800\uba85\u003e\\AppData\\Local\\Temp`\n * `C:\\Users\\\u003c\uc720\uc800\uba85\u003e\\AppData\\Roaming`\n2. **AI Server\uc758 \ub85c\uadf8 \ud30c\uc77c \uacbd\ub85c**: AI Server\uc758 \ub85c\uadf8 \ud30c\uc77c \uacbd\ub85c\ub294 AI Server\uc758 \uc124\uce58 \uc704\uce58\ub098 \uc124\uc815\ud30c\uc77c\uc5d0 \ub098\uc640 \uc788\uc2b5\ub2c8\ub2e4. \ubcf4\ud1b5\uc740 `log` \ud3f4\ub354\ub098 `logs` \ud3f4\ub354\uc5d0\uc11c \ucc3e\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n3. **\ub85c\uadf8 \ud30c\uc77c \uad00\ub9ac \ub3c4\uad6c**: \ub9ce\uc740 AI Server \uc81c\ud488\uc5d0\uc11c \ub85c\uadf8 \ud30c\uc77c \uad00\ub9ac\ub97c \uc704\ud55c \ub3c4\uad6c\uac00 \uc81c\uacf5\ub429\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, NVIDIA\uc758 Deep Learning SDK\ub294 `nvidia-smi` \uba85\ub839\uc5b4\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub85c\uadf8 \ud30c\uc77c\uc744 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n4. **SSH\ub098 \ud30c\uc77c \uc804\uc1a1 \ub85c\uadf8 \ud655\uc778**: AI Server\uc640 \uc5f0\uacb0\ub41c SSH \uc138\uc158\uc744 \ud1b5\ud574 \ub85c\uadf8 \ud30c\uc77c\uc744 \ud655\uc778\ud558\uac70\ub098, \ub85c\uadf8 \ud30c\uc77c\uc744 \ud30c\uc77c \uc804\uc1a1 \ub85c\uadf8\ub85c \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n5. **AI Server \uc778\ud130\ud398\uc774\uc2a4**: AI Server \uc778\ud130\ud398\uc774\uc2a4\ub97c \ud1b5\ud574 \ub85c\uadf8 \ud30c\uc77c\uc744 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc608\ub97c \ub4e4\uc5b4, NVIDIA\uc758 Deep Learning SDK\ub294 `nvidia-smi log` \uba85\ub839\uc5b4\ub97c \uc0ac\uc6a9\ud558\uc5ec \ub85c\uadf8 \ud30c\uc77c\uc744 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.\n\nAI Server \uc720\ud615\uc5d0 \ub530\ub77c \ub85c\uadf8 \ud30c\uc77c \ud655\uc778 \ubc29\ubc95\uc774 \ub2ec\ub77c\uc9c8 \uc218 \uc788\uc73c\uba70, AI Server\uc758 \uc124\uce58 \uac00\uc774\ub4dc\ub098 \ubb38\uc11c\ub97c \ucc38\uace0\ud558\uc5ec \ub85c\uadf8 \ud30c\uc77c \ud655\uc778 \ubc29\ubc95\uc744 \ud655\uc778\ud558\uc2dc\ub294 \uac83\uc774 \uc88b\uc2b5\ub2c8\ub2e4.\n\n### \uc608\uc2dc \ucf54\ub4dc (Python)\n```python\nimport os\n\n# \ub85c\uadf8 \ud30c\uc77c \uacbd\ub85c \uc9c0\uc815\nlog_dir = \u0027/path/to/log/files\u0027\n\n# \ub85c\uadf8 \ud30c\uc77c \ubaa9\ub85d \uc5f4\uae30\nlog_files = os.listdir(log_dir)\n\n# \ub85c\uadf8 \ud30c\uc77c \ucf58\ud150\uce20\ub97c \uc77d\uae30\nfor file in log_files:\n    file_path = os.path.join(log_dir, file)\n    with open(file_path, \u0027r\u0027) as f:\n        print(f.read())\n```\n\n### \uc608\uc2dc \uba85\ub839\uc5b4 (Linux)\n```bash\n# \ub85c\uadf8 \ud30c\uc77c \uacbd\ub85c \uc9c0\uc815\nlog_dir=/path/to/log/files\n\n# \ub85c\uadf8 \ud30c\uc77c \ubaa9\ub85d \ud655\uc778\nls $log_dir\n\n# \ub85c\uadf8 \ud30c\uc77c \ucf58\ud150\uce20 \ud655\uc778\ncat $log_dir/\ud30c\uc77c\uc774\ub984.log\n```",
    "prompt": "\uc5b4\ub5bb\uac8c AI Server\uc5d0 \ub85c\uadf8 \ud30c\uc77c\uc744 \ud655\uc778\ud558\ub098\uc694?"
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("zomd/my-distiset-ba327a12", "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("zomd/my-distiset-ba327a12")
```


</details>




