huggingartists/baklan
Text Generation • Updated • 7
text stringclasses 3
values |
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Hush!
Or make a sound
If you willing to die in vain
Rush!
It’s now or never
If you going to touch the flame
My gosh!
You shouldnt see it
Now we run out of time
I will force you to listen
No way to beat it
They will suck out your mind
But the pain will subside
You can’t tell what youre missing
The heavens hear us
The de... |
Ти не любила зірвані квіти
Розчинну каву, вітер та сухе вино
Тебе ще міг я довго терпіти
Але повір, що зараз мені все одно
Ще темрявою смуток на серці
Хоч сонце ясно світить у моє вікно
Усе хотів я з пам’яті стерти
Та кожен раз у снах я бачу це кіно
Я наче ніч прийду
Та замету свої сліди
Ти пожалкуєш, що
Спалила всі мо... |
Е, конча
Еа
Йоу
Мне приснилось что нужно купить губки для мытья посуды
Проснулся, а они
Биопсия мозга
менту череп за пачку винстона
В моём кармане пакет насвая
Я его кидаю и это обожаю
Жму 200 летают над тобою
Ты будешь- говоришь что не сосёшь аналистам, уважаю
Но нагибаюсь за мылом
Мать моя, после школы было здорово... |
Dataset Card for "huggingartists/baklan"
Dataset Summary
The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available here.
Supported Tasks and Leaderboards
Languages
en
How to use
How to load this dataset directly with the datasets library:
from datasets import load_dataset
dataset = load_dataset("huggingartists/baklan")
Dataset Structure
An example of 'train' looks as follows.
This example was too long and was cropped:
{
"text": "Look, I was gonna go easy on you\nNot to hurt your feelings\nBut I'm only going to get this one chance\nSomething's wrong, I can feel it..."
}
Data Fields
The data fields are the same among all splits.
text: astringfeature.
Data Splits
| train | validation | test |
|---|---|---|
| 3 | - | - |
'Train' can be easily divided into 'train' & 'validation' & 'test' with few lines of code:
from datasets import load_dataset, Dataset, DatasetDict
import numpy as np
datasets = load_dataset("huggingartists/baklan")
train_percentage = 0.9
validation_percentage = 0.07
test_percentage = 0.03
train, validation, test = np.split(datasets['train']['text'], [int(len(datasets['train']['text'])*train_percentage), int(len(datasets['train']['text'])*(train_percentage + validation_percentage))])
datasets = DatasetDict(
{
'train': Dataset.from_dict({'text': list(train)}),
'validation': Dataset.from_dict({'text': list(validation)}),
'test': Dataset.from_dict({'text': list(test)})
}
)
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
Citation Information
@InProceedings{huggingartists,
author={Aleksey Korshuk}
year=2021
}
About
Built by Aleksey Korshuk
For more details, visit the project repository.
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Models trained or fine-tuned on huggingartists/baklan