Dataset Card for spacelm-corpus

This dataset has been created with distilabel.

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/daniazie/spacelm-corpus/raw/main/pipeline.yaml"

or explore the configuration:

distilabel pipeline info --config "https://huggingface.co/datasets/daniazie/spacelm-corpus/raw/main/pipeline.yaml"

Dataset structure

The examples have the following structure per configuration:

Configuration: default

---

{
    "distilabel_metadata": {
        "raw_input_evol_instruct_0": null,
        "raw_input_text_generation_0": null,
        "raw_input_text_generation_1": null,
        "raw_output_evol_instruct_0": null,
        "raw_output_text_generation_0": null,
        "raw_output_text_generation_1": null
    },
    "instruction": null,
    "model_name": null,
    "response": null
}

This subset can be loaded as:

from datasets import load_dataset

ds = load_dataset("daniazie/spacelm-corpus", "default")

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

from datasets import load_dataset

ds = load_dataset("daniazie/spacelm-corpus")

References

@misc{xu2023wizardlmempoweringlargelanguage,
    title={WizardLM: Empowering Large Language Models to Follow Complex Instructions},
    author={Can Xu and Qingfeng Sun and Kai Zheng and Xiubo Geng and Pu Zhao and Jiazhan Feng and Chongyang Tao and Daxin Jiang},
    year={2023},
    eprint={2304.12244},
    archivePrefix={arXiv},
    primaryClass={cs.CL},
    url={https://arxiv.org/abs/2304.12244},
}