| import json |
| import datasets |
|
|
| |
| |
| _DESCRIPTION = """\ |
| A high-quality dataset for efficient instruction tuning. |
| """ |
|
|
| |
| _HOMEPAGE = "" |
|
|
| |
| _LICENSE = "other" |
|
|
| |
| |
| |
| _URLS = { |
| } |
|
|
|
|
| class LimaConfig(datasets.BuilderConfig): |
| """BuilderConfig""" |
|
|
| def __init__(self, **kwargs): |
| """BuilderConfig |
| Args: |
| **kwargs: keyword arguments forwarded to super. |
| """ |
| super(LimaConfig, self).__init__(**kwargs) |
|
|
|
|
| class Lima(datasets.GeneratorBasedBuilder): |
|
|
| BUILDER_CONFIGS = [ |
| LimaConfig( |
| name="plain_text", |
| version=datasets.Version("0.0.1", ""), |
| description="Plain text", |
| ), |
| ] |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features( |
| { |
| "conversations": datasets.features.Sequence(datasets.Value("string")), |
| "source": datasets.Value("string"), |
| } |
| ), |
| ) |
|
|
| def _split_generators(self, dl_manager): |
| return [ |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": dl_manager.download("train.jsonl")}), |
| datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath":dl_manager.download("test.jsonl")}) |
| ] |
|
|
| def _generate_examples(self, filepath): |
| """This function returns the examples in the raw (text) form.""" |
| key = 0 |
| with open(filepath) as f: |
| for line in f.readlines(): |
| instance = json.loads(line) |
| yield key, instance |
| key += 1 |