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).
source languages: en
target languages: tw
Live Demo Open in Colab Download Copy S3 URI
How to use
from sparknlp.pretrained import PretrainedPipeline
pipeline = PretrainedPipeline("translate_en_tw", lang = "xx")
pipeline.annotate("Your sentence to translate!")
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("translate_en_tw", lang = "xx")
pipeline.annotate("Your sentence to translate!")
import nlu
text = ["text to translate"]
translate_df = nlu.load('xx.English.translate_to.Twi').predict(text, output_level='sentence')
translate_df
Model Information
| Model Name: | translate_en_tw |
| Type: | pipeline |
| Compatibility: | Spark NLP 3.1.0+ |
| License: | Open Source |
| Edition: | Official |
| Language: | xx |
Data Source
https://github.com/Helsinki-NLP/OPUS-MT-train/tree/master/models
Included Models
- DocumentAssembler
- SentenceDetectorDLModel
- MarianTransformer