metadata

datasets:
  - Helsinki-NLP/tatoeba
language:
  - ko
  - en
metrics:
  - bleu
  - chrf
pipeline_tag: translation
library_name: transformers

Model info

Distilled model from a Tatoeba-MT Teacher: Tatoeba-MT-models/kor-eng/opusTCv20210807-sepvoc_transformer-big_2022-07-28, which has been trained on the Tatoeba dataset.

We used the OpusDistillery to train new a new student with the tiny architecture, with a regular transformer decoder. For training data, we used Tatoeba. The configuration file fed into OpusDistillery can be found here.

How to run

>>> from transformers import pipeline

>>> pipe = pipeline("translation", model="odegiber/ko-en", max_length=256)
>>> pipe("2017년 말, 시미노프는 쇼핑 텔레비젼 채널인 QVC에 출연했다.")
[{'translation_text': 'At the end of 2017, Siminof appeared on the shopping television channel QVC.'}]

Benchmarks

testset	BLEU	chr-F
flores200	20.3	50.3