Japanese GPT2 Lyric Model
Model description
The model is used to generate Japanese lyrics.
How to use
import torch
from transformers import T5Tokenizer, GPT2LMHeadModel
device = torch.device("cpu")
if torch.cuda.is_available():
device = torch.device("cuda")
tokenizer = T5Tokenizer.from_pretrained("skytnt/gpt2-japanese-lyric-medium")
model = GPT2LMHeadModel.from_pretrained("skytnt/gpt2-japanese-lyric-medium")
model = model.to(device)
def gen_lyric(title: str, prompt_text: str):
if len(title)!= 0 or len(prompt_text)!= 0:
prompt_text = "<s>" + title + "[CLS]" + prompt_text
prompt_text = prompt_text.replace("\n", "\\n ")
prompt_tokens = tokenizer.tokenize(prompt_text)
prompt_token_ids = tokenizer.convert_tokens_to_ids(prompt_tokens)
prompt_tensor = torch.LongTensor(prompt_token_ids)
prompt_tensor = prompt_tensor.view(1, -1).to(device)
else:
prompt_tensor = None
# model forward
output_sequences = model.generate(
input_ids=prompt_tensor,
max_length=512,
top_p=0.95,
top_k=40,
temperature=1.0,
do_sample=True,
early_stopping=True,
bos_token_id=tokenizer.bos_token_id,
eos_token_id=tokenizer.eos_token_id,
pad_token_id=tokenizer.pad_token_id,
num_return_sequences=1
)
# convert model outputs to readable sentence
generated_sequence = output_sequences.tolist()[0]
generated_tokens = tokenizer.convert_ids_to_tokens(generated_sequence)
generated_text = tokenizer.convert_tokens_to_string(generated_tokens)
generated_text = "\n".join([s.strip() for s in generated_text.split('\\n')]).replace(' ', '\u3000').replace('<s>', '').replace('</s>', '\n\n---end---')
title_and_lyric = generated_text.split("[CLS]",1)
if len(title_and_lyric)==1:
title,lyric = "" , title_and_lyric[0].strip()
else:
title,lyric = title_and_lyric[0].strip(), title_and_lyric[1].strip()
return f"---{title}---\n\n{lyric}"
print(gen_lyric("桜",""))
Training data
Training data contains 143,587 Japanese lyrics which are collected from uta-net by lyric_download
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