|
""" |
|
### Spanish Poetry Dataset ### |
|
Collection of Spanish poems retrieved by Andrea Morales and Miguel L贸pez from the website www.poemas-del-alma.com |
|
Corpus adapted for Causal Language Modeling (CLM) to train GPT-like models. The author and title of each poem has been removed. |
|
Note that, depending on your tokenizer, you might want to replace the <BOS>/<SEP>/<EOS> tokens by <|endoftext|> or something else. |
|
Also note that the number of rows is slightly lower than the original dataset (andreamorgar/spanish_poetry) because a few incorrect examples have been filtered out. |
|
""" |
|
|
|
import datasets |
|
|
|
_DESCRIPTION = "Collection of Spanish poems retrieved from www.poemas-del-alma.com" |
|
_HOMEPAGE = "https://www.kaggle.com/datasets/andreamorgar/spanish-poetry-dataset" |
|
_AUTHORS = "Andrea Morales and Miguel L贸pez" |
|
_LICENSE = "GNU Lesser General Public License" |
|
|
|
class Poemas(datasets.GeneratorBasedBuilder): |
|
def _info(self): |
|
features = datasets.Features( |
|
{ |
|
"text": datasets.Value("string"), |
|
} |
|
) |
|
return datasets.DatasetInfo( |
|
description=_DESCRIPTION, |
|
features=features, |
|
homepage=_HOMEPAGE, |
|
license=_LICENSE, |
|
citation=_AUTHORS, |
|
) |
|
|
|
def _split_generators(self, dl_manager): |
|
data_file = dl_manager.download_and_extract("poemas.txt") |
|
return [ |
|
datasets.SplitGenerator( |
|
name=datasets.Split.TRAIN, |
|
gen_kwargs={ |
|
"filepath": data_file, |
|
"split": "train", |
|
}, |
|
) |
|
] |
|
|
|
def _generate_examples(self, filepath, split): |
|
to_replace = {"<BOS>": "", "<EOS>": "", "<SEP>": "\n"} |
|
with open(filepath, encoding="utf-8") as f: |
|
for key, poem in enumerate(f.readlines()): |
|
for old,new in to_replace.items(): |
|
poem = poem.replace(old, new) |
|
yield key, {"text": poem.strip()} |
|
|