huggingartists/suicideoscope
Text Generation
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Vanity was a vain subject from the start
Everything that is given is just luck
But time wont do me justice just enough
Its time to shorten my biography
For the name of genius
Time wont do me justice enough
For dying doesnt nearly interest me
As much as killing myself
Theres something attractive about control
Even though artificial
Final thoughts on final days
I cant wait to stretch my legs on suns warm surface
Cat got my tongue eyes mind sighs
And took them away
Blindfolded circus jump for help
Off a tall structure figurehead
The facts and blood and everything
Hit me over and over as i become
Even less sober and shrink lonely
In a narrow grey corner
The facts and blood and everything
Hit me over and over as i become
Even less sober and shrink lonely
In a narrow grey corner |
Lets start the day
Grin out a smile
And get over with it
Just because
Isnt an abyss merely
A well
Too lengthy for a single mans lifespan
Third person vision
Makes no sense whatsoever
It questions and questions the
Unresolved levels of cognitive endeavors
She licked up the blood as it was still
Oozing from her body
Blood runs deep in
Cigarette bums and or
Other sorts of bums
Do you
By any chance
Value your life
Gets me every time
Not having problems is so
The environment speaks for itself
Need now i mediate
Existence is trivial
Existence is trivial
Existence is trivial
Existence is trivial
Existence is a trivial phase
Nothingness is my ultimate gain
As a subject im viewed neutrally
But as a human being
Thats a different subject entirely |
So you think thats pretty clever
You should listen to me in my sleep
Not that i could sleep when youre near
So you think thats pretty clever
You should listen to me in my sleep
You really should sleep you know
So you guess thats pretty clever
Yeah i guess
I guess i should really harm myself
Like really really mess it up
Cause you see its so much fun
Not that im no mess to start with
Looking at you its hard to accept that corpses are true
And you will be one lying face up
Or shredded in pieces somewhere in an accident
Your absence more visible than presence is sending me
Bleak blue messengers
Serving me the reality genes
And poisonous sleeps |
Were wailing and wailing
Test of the city
See you in the car
See you seen the car
To the cards to cartoons it spins
One two buckle my shoe
Three four on the floor
One two buckle my shoe
Three four dragged by misdemeanor
Oh seven new student
Sins go first at restaurants
Many times missed stuck on the grand scheme of the world
Meet you at the altar
Meet you at the altar
Melted churches cruising
One two buckle my shoe
Three four on the floor
Five six through my heart and down my ribs
I pierce my vital limbs
Choke you a little bit in my car
With the seatbelts
Oh hang in there hun
All tied up
I only wanted love
I only want love
Choke you a little bit in my car
With the seatbelts
Oh hang in there hun
All tied up
I only wanted love
I only want love
Choke you a little bit in my car
With the seatbelts
Oh hang in there hun
All tied up
I only wanted love
I only want love
Im learning when to stop
Im learning when to stop
Untie my shoes and hope to fall
Untie my shoes and hope to fall
Im learning when to stop |
Chlorocyanide smothered me good any day
Got me way way all the way and satisfied
Up until the rays of your forms sprayed my weary eyes
I figured i should go ahead and give it a try
Not gonna lie conversing felt confusing
Especially in an empty football stadium and losing hard
The americans really did it this time
Weve been blown ten billion miles high
But i only wanted you for the chemical
For the chemical reactions in my head
I only wanted you for the chemical
For the chemical reactions in my head
Future was filled with hollywood endings
I couldnt help but gag and wish for a way out
How about some big old new years eve fireworks
Deliberately frying up our cables
And the images of each other out of one another
Because i only wanted you for the chemical
For the chemical reactions in my head
I only wanted you for the chemical
For the chemical reactions in my head |
EDing on your first
ODing right before your last
Dismiss high hopes of trying to
Redefine your past self
Among the unable to comprehend what youre painting
You are EDing on your first
ODing right before your last
You loathe your peers and sneezed
They only cringed and laughed
You wasted trash lashed
You are fucking frozen in time by a wave
Of unfiltered nonchalance
Your blood crystalizes and you die
Of the methods you could do to yourself
Turn your head and meet me
We were on earth to learn
We were on earth to learn
We were on earth to learn
We were on earth to learn
We were on earth to learn
We were on earth to learn
We were on earth to learn
We were on earth to learn
Dream steps out of this world
To avoid to
To avoid to endure
Dream steps out of this world
To avoid to
To avoid to endure |
You dont seem to see the seas
I knew its disappointing to make assumptions
I knew the news before they were loose
And its only the first glance thats amusing
You dont seem to see the seas
Dawdling around pointlessly at ease oh please
No doctor could help
Its not a curable disease
You dont seem to see the seas
Border of living and deceased
Sparsely on our backs we throw our arms around in search
I throw my arms in search of
I had been too certain
That something will take away my sorrows place
But in this lighting
All lightness light
Saved words
Unused words
Were kept for nothing
Im in the oceans
Having a leisure
Tasting the imagined shining of suns
Captured by leisure
Tasting the imagined shining of suns |
The Lyrics dataset parsed from Genius. This dataset is designed to generate lyrics with HuggingArtists. Model is available here.
en
How to load this dataset directly with the datasets library:
from datasets import load_dataset
dataset = load_dataset("huggingartists/suicideoscope")
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..."
}
The data fields are the same among all splits.
text
: a string
feature.train | validation | test |
---|---|---|
11 | - | - |
'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/suicideoscope")
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)})
}
)
@InProceedings{huggingartists,
author={Aleksey Korshuk}
year=2021
}
Built by Aleksey Korshuk
For more details, visit the project repository.