HeyLucasLeao/gpt-neo-small-emo-lyrics

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Emo Bot

Model Description

This is a finetuned version from GPT-Neo-125M for Generating Music Lyrics by Emo Genre.

Training data

It was trained with 2381 songs by 15 bands that were important to emo culture in the early 2000s, not necessary directly playing on the genre.

Training Procedure

It was finetuned using the Trainer Class available on the Hugging Face library.

Learning Rate: 2e-4

Epochs: 40

Colab for Finetuning: https://colab.research.google.com/drive/1jwTYI1AygQf7FV9vCHTWA4Gf5i--sjsD?usp=sharing

Colab for Testing: https://colab.research.google.com/drive/1wSP4Wyr1-DTTNQbQps_RCO3ThhH-eeZc?usp=sharing

Goals

My true intention was totally educational, thus making available a this version of the model as a example for future proposes.

How to use

from transformers import AutoTokenizer, AutoModelForCausalLM
import re

if torch.cuda.is_available():
    device = torch.device('cuda')
else:
    device = torch.device('cpu')
print(device)

tokenizer = AutoTokenizer.from_pretrained("HeyLucasLeao/gpt-neo-small-emo-lyrics")
model = AutoModelForCausalLM.from_pretrained("HeyLucasLeao/gpt-neo-small-emo-lyrics")
model.to('cuda')

generated = tokenizer('I miss you',return_tensors='pt').input_ids.cuda()

#Generating texts
sample_outputs = model.generate(generated, 
                 # Use sampling instead of greedy decoding 
                 do_sample=True, 
                 # Keep only top 3 token with the highest probability
                 top_k=10, 
                 # Maximum sequence length
                 max_length=200, 
                 # Keep only the most probable tokens with cumulative probability of 95%
                 top_p=0.95, 
                 # Changes randomness of generated sequences
                 temperature=2.,
                 # Number of sequences to generate                 
                 num_return_sequences=3)
                 
# Decoding and printing sequences
for i, sample_output in enumerate(sample_outputs):
    texto = tokenizer.decode(sample_output.tolist())
    regex_padding = re.sub('<|pad|>', '', texto)
    regex_barra = re.sub('[|+]', '', regex_padding)
    espaço = re.sub('[ +]', ' ', regex_barra)
    resultado = re.sub('[\n](2, )', '\n', espaço)
    print(">> Text {}: {}".format(i+1, resultado + '\n'))
  
""">> Texto 1: I miss you 
 I miss you more than anything 
 And if you change your mind 
 I do it like a change of mind 
 I always do it like theeah 
 Everybody wants a surprise 
 Everybody needs to stay collected 
 I keep your locked and numbered 
 Use this instead: Run like the wind 
 Use this instead: Run like the sun 
 And come back down: You've been replaced 
 Don't want to be the same 
 Tomorrow 
 I don't even need your name 
 The message is on the way 
 make it while you're holding on 
 It's better than it is 
 Everything more security than a parade 
 Im getting security 
angs the world like a damned soul 
 We're hanging on a queue 
 and the truth is on the way 
 Are you listening? 
 We're getting security 
 Send me your soldiers 
 We're getting blood on"""

""">> Texto 2: I miss you 
 And I could forget your name 
 All the words we'd hear 
 You miss me 
 I need you 
 And I need you 
 You were all by my side 
 When we'd talk to no one 
 And I 
 Just to talk to you 
 It's easier than it has to be 
 Except for you 
 You missed my know-all 
 You meant to hug me 
 And I 
 Just want to feel you touch me 
 We'll work up 
 Something wild, just from the inside 
 Just get closer to me 
 I need you 
 You were all by my side 
 When we*d talk to you 
, you better admit 
 That I'm too broken to be small 
 You're part of me 
 And I need you 
 But I 
 Don't know how 
 But I know I need you 
 Must"""

""">> Texto 3: I miss you 
 And I can't lie 
 Inside my head 
 All the hours you've been through 
 If I could change your mind 
 I would give it all away 
 And I'd give it all away 
 Just to give it away 
 To you 
 Now I wish that I could change 
 Just to you 
 I miss you so much 
 If I could change 
 So much 
 I'm looking down 
 At the road 
 The one that's already been 
 Searching for a better way to go 
 So much I need to see it clear 
  topk  wish me an ehive 
 I wish I wish I wish I knew 
 I can give well 
 In this lonely night 
 
 The lonely night 
 I miss you 
 I wish it well  
 If I could change   
 So much 
 I need you"""