Description
Marian is an efficient, free Neural Machine Translation framework written in pure C++ with minimal dependencies. It is mainly being developed by the Microsoft Translator team. Many academic (most notably the University of Edinburgh and in the past the Adam Mickiewicz University in Poznań) and commercial contributors help with its development.
It is currently the engine behind the Microsoft Translator Neural Machine Translation services and being deployed by many companies, organizations and research projects (see below for an incomplete list).
Note that this is a very computationally expensive module especially on larger sequence. The use of an accelerator such as GPU is recommended.
-
source languages:
zls -
target languages:
en
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("translate_zls_en", lang = "xx")
pipeline.annotate("Your sentence to translate!")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("translate_zls_en", lang = "xx")
pipeline.annotate("Your sentence to translate!")
import nlu
text = ["text to translate"]
translate_df = nlu.load('xx.zls.translate_to.en').predict(text, output_level='sentence')
translate_df
Model Information
| Model Name: | translate_zls_en |
| Type: | pipeline |
| Compatibility: | Spark NLP 2.7.0+ |
| Edition: | Official |
| Language: | xx |
Data Source
https://github.com/Helsinki-NLP/OPUS-MT-train/tree/master/models