README.md

metadata

language: ja
tags:
  - ja
  - japanese
  - gpt2
  - text-generation
  - lm
  - nlp
license: mit
widget:
  - text: 桜が咲く

Japanese GPT2 Lyric Model

Model description

The model is used to generate Japanese lyrics.

You can try it on my website https://lyric.fab.moe/

How to use

import torch
from transformers import T5Tokenizer, GPT2LMHeadModel

tokenizer = T5Tokenizer.from_pretrained("skytnt/gpt2-japanese-lyric-small")
model = GPT2LMHeadModel.from_pretrained("skytnt/gpt2-japanese-lyric-small")


def gen_lyric(prompt_text: str):
    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)
    # 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>', '\n\n---end---')
    return generated_text


print(gen_lyric("桜が咲く"))

Training data

Training data contains 143,587 Japanese lyrics which are collected from uta-net by lyric_download