| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline | |
| import torch | |
| model = AutoModelForSeq2SeqLM.from_pretrained("KarmaCST/nllb-200-distilled-600M-dz-to-en") | |
| tokenizer = AutoTokenizer.from_pretrained("KarmaCST/nllb-200-distilled-600M-dz-to-en") | |
| src_lang = "dzo_Tibt" | |
| tgt_lang = "eng_Latn" | |
| 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 Sentence", placeholder = " Enter Dzongkha sentence here ...") | |
| ], | |
| ["text"], | |
| ).launch() |