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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline | |
import torch | |
model_checkpoint = "japanese-denim/mbart-50-finetuned-eng-to-naga" | |
model = AutoModelForSeq2SeqLM.from_pretrained(model_checkpoint) | |
tokenizer = AutoTokenizer.from_pretrained(model_checkpoint) | |
src_lang = 'en_XX' | |
tgt_lang = "ng_XX" | |
def translate(text): | |
translation_pipeline = pipeline("translation", | |
model=model, | |
tokenizer=tokenizer, | |
src_lang=src_lang, | |
tgt_lang=tgt_lang) | |
result = translation_pipeline(text) | |
return result[0]['translation_text'] | |
gr.Interface( | |
translate, | |
[ | |
gr.components.Textbox(label="input", placeholder = " Enter English sentence here") | |
], | |
["text"], | |
).launch() |