README.md

---
license: bigscience-openrail-m
language:
- zh
pipeline_tag: text2text-generation
thumbnail: Chinese Lyrics Generation with Masked Sequence-to-Sequence Pretraining.
---

# Chinese Generation with Masked Sequence-to-Sequence Pretraining

This repository demostrates a format-controllable Chinese lyric generator, fine-tuned on [Chinese-Lyric-Corpus](https://github.com/gaussic/Chinese-Lyric-Corpus) using a [MASS](https://arxiv.org/abs/1905.02450)-like strategy.

# Usage

## Initialization

```python
from transformers import MT5ForConditionalGeneration, MT5Tokenizer, Text2TextGenerationPipeline
model_path = "zake7749/chinese-lyrics-generation-mass"
model = MT5ForConditionalGeneration.from_pretrained(model_path)
tokenizer = MT5Tokenizer.from_pretrained(model_path)
pipe = Text2TextGenerationPipeline(model=model, tokenizer=tokenizer)
```

## Generate lyrics with a template

```python
template = "風花雪月。像XXXXXXXXXX。日升月落。仿若XXXXXXXXXX。"
lyric = pipe(template, max_length=128, top_p=0.8, do_sample=True, repetition_penalty=1.2)[0]['generated_text']
print(lyric) # 風花雪月。像你在我的夢裡慢慢散落。日升月落。仿若我宿命無法陪隨你走過。


template = "XXXXXXX留戀。XXXXXXX。XXX燈火XXXX。XXX手牽手XXXX。"
lyric = pipe(template, max_length=128, top_p=0.8, do_sample=True, repetition_penalty=1.2)[0]['generated_text']
print(lyric) # 我們說好一生不留戀。我們相約在夏天。我們的燈火相偎相牽。我們說好手牽手到永遠。

```

## Acrostic

```python
template = "分XXXXXX。手XXXXXXXXX。之XXXXXXX。後XXXXXXXXX。"
lyric = pipe(template, max_length=128, top_p=0.8, do_sample=True, repetition_penalty=1.2)[0]['generated_text']
print(lyric) # 分開後激情浮現。手牽著手走過的那一天。之間有太多的危險。後悔一點點,傷心一片。
```

## Completion

```python
template = "餘生的光陰牽你手前行。我們共赴一場光年的旅行。XXXXXXXXXX。XXXXXXXXXXXX。"
lyric = pipe(template, max_length=128, top_p=0.8, do_sample=True, repetition_penalty=1.2)[0]['generated_text']
print(lyric) # 餘生的光陰牽你手前行。我們共赴一場光年的旅行。走過的經歷新舊的記憶。都是帶著珍珠淚水無法代替。
```

## Random Generation 

```python
import random

num_example = 5
min_sentence_num, max_sentence_num = 2, 5
min_characher_num, max_character_num = 4, 10

for example_id in range(num_example):
    num_sentences = random.randint(min_sentence_num,  max_sentence_num)
    num_words = ["X" * random.randint(min_characher_num, max_character_num)
                 for _ in range(num_sentences)]

    template = "。".join(num_words) + "。"
    lyric = pipe(template, max_length=128, top_p=0.8, do_sample=True, repetition_penalty=1.2)[0]['generated_text']
    print(f"{example_id + 1}. {lyric}")

# 1. 愛不愛我。讓自己難過。你的擁抱是那麼多。
# 2. 那一天我們重相見。你已站在那個熟悉的街邊。讓我魂牽夢繞在肩。有你的明天。不再留戀。飛過天邊。
# 3. 誰知我們入骨的相思。深深地被俘虜。苦澀滋味含在茶中傾訴。餘情未了落幕。愛到痛處奢望幸福。
# 4. 為什麼你一直讓我傷心。總覺得對你太著迷。
# 5. 一點可憐。還在期待你會出現。哪怕只是匆匆一眼。
```

# Note

1. The model is still under training, so sometimes it might not follow the template explicitly, especially for long sequences generation.
2. The model would output `,` as a pause in the lyric, for example `我的愛,像潮水。`. If you don't need the pause, you can add the id of `,` to `bad_words_ids`.
3. The model was only fine-tuned on traditional Chinese corpus which leads to a bit unstable performance in simplified Chinese.
4. When there are no/few keywords in the given input, the model may **combine snippets from real world songs** to fit the template. 

# Disclaimer

This lyric generator is for academic purposes only. Users of this model should exercise caution and carefully evaluate the results before using them for any commercial or non-academic purpose. We are not liable for any damages or losses resulting from the use or misuse of the model.