Dataset Card for uplimit-synthetic-data-week-1-with-multi-turn

This dataset has been created with distilabel.

The pipeline script was uploaded to easily reproduce the dataset: colab_kernel_launcher.py.

It can be run directly using the CLI:

distilabel pipeline run --script "https://huggingface.co/datasets/85danf/uplimit-synthetic-data-week-1-with-multi-turn/raw/main/colab_kernel_launcher.py"

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:

distilabel pipeline run --config "https://huggingface.co/datasets/85danf/uplimit-synthetic-data-week-1-with-multi-turn/raw/main/pipeline.yaml"

or explore the configuration:

distilabel pipeline info --config "https://huggingface.co/datasets/85danf/uplimit-synthetic-data-week-1-with-multi-turn/raw/main/pipeline.yaml"

Dataset structure

The examples have the following structure per configuration:

Configuration: default

---

{
    "conversation": [
        {
            "content": "I\u0027m planning a trip to Japan and I\u0027m interested in visiting Tokyo. I\u0027ve heard that Tokyo is a city that\u0027s full of contrasts, and I\u0027m excited to experience the traditional and modern aspects of the city. I\u0027d like to know more about the different neighborhoods to visit in Tokyo. What are some must-visit neighborhoods to consider?\n\nI\u0027m particularly interested in exploring the traditional side of Tokyo, and I\u0027d like to know about the Asakusa district, which I\u0027ve heard is a great place to experience the old Japan.",
            "role": "user"
        },
        {
            "content": "You\u0027re in for a treat! Tokyo is indeed a city of contrasts, and exploring its different neighborhoods is a big part of the fun. Asakusa is an excellent choice for experiencing traditional Japan, and I\u0027d be happy to tell you more about it.\n\nAsakusa is one of the oldest districts in Tokyo, with a rich history dating back to the 15th century. It\u0027s a great place to immerse yourself in traditional Japanese culture, and it\u0027s still relatively unchanged from the old days. Here are some must-visit spots in Asakusa:\n\n1. Senso-ji Temple: This iconic Buddhist temple is the",
            "role": "assistant"
        },
        {
            "content": "...iconic symbol of Asakusa and one of the most famous temples in Japan. It\u0027s a must-visit attraction, and it\u0027s a great place to experience traditional Japanese culture. The temple is famous for its giant paper lantern, Nakamise Shopping Street, and the nearby Nakamise Shopping Street, which is a historic shopping street filled with traditional snacks, souvenirs, and local goods.\n\n2. Sumida River: Asakusa is situated on the banks of the Sumida River, which offers beautiful views of the Tokyo Skytree and the city skyline. You can take a stroll along the river and enjoy the scenery",
            "role": "user"
        },
        {
            "content": "You\u0027re absolutely right about Senso-ji Temple and Nakamise Shopping Street being must-visit attractions in Asakusa. The giant paper lantern, known as the \"Kaminarimon,\" is a iconic symbol of the temple and a great spot for photos.\n\nAnd yes, the Nakamise Shopping Street is a great place to experience traditional Japanese culture and shop for souvenirs. You can find all sorts of traditional snacks, such as senbei (soy sauce-flavored crackers) and ningyo-yaki (small cakes filled with red bean paste), as well as local goods like handmade crafts and traditional clothing.\n\nAs for",
            "role": "assistant"
        }
    ],
    "distilabel_metadata": {
        "statistics_magpie_generator_0": {
            "input_tokens": [
                85,
                193,
                331,
                459
            ],
            "output_tokens": [
                109,
                128,
                128,
                128
            ]
        }
    },
    "model_name": "https://api-inference.huggingface.co/models/meta-llama/Llama-3.2-3B-Instruct"
}

This subset can be loaded as:

from datasets import load_dataset

ds = load_dataset("85danf/uplimit-synthetic-data-week-1-with-multi-turn", "default")

Or simply as it follows, since there's only one configuration and is named default:

from datasets import load_dataset

ds = load_dataset("85danf/uplimit-synthetic-data-week-1-with-multi-turn")

References

@misc{xu2024magpiealignmentdatasynthesis,
    title={Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing},
    author={Zhangchen Xu and Fengqing Jiang and Luyao Niu and Yuntian Deng and Radha Poovendran and Yejin Choi and Bill Yuchen Lin},
    year={2024},
    eprint={2406.08464},
    archivePrefix={arXiv},
    primaryClass={cs.CL},
    url={https://arxiv.org/abs/2406.08464},
}