quickmt-zh-en Neural Machine Translation Model

quickmt-zh-en is a reasonably fast and reasonably accurate neural machine translation model for translation from zh into en.

Model Information

• Trained using eole
• 200M parameter transformer 'big' with 8 encoder layers and 2 decoder layers
• Separate source and target Sentencepiece tokenizers
• Exported for fast inference to CTranslate2 format
• Training data: https://huggingface.co/datasets/quickmt/quickmt-train.zh-en/tree/main

See the eole model configuration in this repository for further details.

Usage with quickmt

First, install quickmt and download the model

git clone https://github.com/quickmt/quickmt.git
pip install ./quickmt/

quickmt-model-download quickmt/quickmt-zh-en ./quickmt-zh-en

from quickmt import Translator

# Auto-detects GPU, set to "cpu" to force CPU inference
t = Translator("./quickmt-zh-en/", device="auto")

# Translate - set beam size to 5 for higher quality (but slower speed)
t(["他补充道：“我们现在有 4 个月大没有糖尿病的老鼠，但它们曾经得过该病。”"], beam_size=1)

# Get alternative translations by sampling
# You can pass any cTranslate2 `translate_batch` arguments
t(["他补充道：“我们现在有 4 个月大没有糖尿病的老鼠，但它们曾经得过该病。”"], sampling_temperature=1.2, beam_size=1, sampling_topk=50, sampling_topp=0.9)

The model is in ctranslate2 format, and the tokenizers are sentencepiece, so you can use ctranslate2 directly instead of through quickmt. It is also possible to get this model to work with e.g. LibreTranslate which also uses ctranslate2 and sentencepiece.

Metrics

BLEU and CHRF2 calculated with sacrebleu on the Flores200 devtest test set ("zho_Hans"->"eng_Latn"). COMET22 with the comet library and the default model. "Time (s)" is the time in seconds to translate (using ctranslate2) the flores-devtest dataset (1012 sentences) on an RTX 4070s GPU with batch size 32.

Model	bleu	chrf2	comet22	Time (s)
quickmt/quickmt-zh-en	29.36	58.10	0.8655	0.88
Helsinki-NLP/opus-mt-zh-en	23.35	53.60	0.8426	3.78
facebook/m2m100_418M	15.99	50.13	0.7881	16.61
facebook/nllb-200-distilled-600M	26.22	55.18	0.8507	20.89
facebook/m2m100_1.2B	20.30	54.23	0.8206	33.12
facebook/nllb-200-distilled-1.3B	28.56	57.35	0.8620	36.64

quickmt-zh-en is the fastest and highest quality.