| import gradio as gr | |
| import torch | |
| from huggingface_hub import hf_hub_download | |
| from transformers import pipeline | |
| model_checkpoint_nllb = "facebook/nllb-200-distilled-600M" | |
| model_checkpoint_marian_en = "mbarnig/marianNMT-tatoeba-en-lb" | |
| model_checkpoint_marian_lb = "mbarnig/marianNMT-tatoeba-lb-en" | |
| model_checkpoint_t5_mt5 = "mbarnig/T5-mt5-tatoeba-en-lb" | |
| my_title = "🇬🇧 Mir iwwersetzen vun an op Lëtzebuergesch ! 🇫🇷" | |
| my_description = "English-Luxembourgish machine translation (MT) demo based on 3 open-source transformer models: Facebook-NLLB, Microsoft-MarianNMT & Google-T5/mt5." | |
| my_article = "<h3>User guide</h3><p>1. Press the submit button to translate an english text with the default values. 2. Compare the result with the luxembourgish example. 3. Select a model and a translation direction and enter your own text. Have fun !</p><p>Go to <a href='https://www.web3.lu/'>Internet with a Brain</a> to read my french publication <a href='https://www.web3.lu/'>Das Küsschen und die Sonne stritten sich ...</a> about the history of machine translation in Luxembourg from 1975 until today.</p>" | |
| default_input = "The North Wind and the Sun were disputing which was the stronger, when a traveler came along wrapped in a warm cloak." | |
| TRANSLATION_MODELS = [ | |
| "NLLB", | |
| "MarianNMT", | |
| "T5-mt5" | |
| ] | |
| TRANSLATION_DIRECTION = [ | |
| "en -> lb", | |
| "lb -> en" | |
| ] | |
| EXAMPLE = [ | |
| ["An der Zäit hunn sech den Nordwand an d’Sonn gestridden, wie vun hinnen zwee wuel méi staark wier, wéi e Wanderer, deen an ee waarme Mantel agepak war, iwwert de Wee koum", "NLLB", "lb -> en"] | |
| ] | |
| my_inputs = [ | |
| gr.Textbox(lines=5, label="Input", value=default_input), | |
| gr.Radio(label="Translation Model", choices = TRANSLATION_MODELS, value = "NLLB"), | |
| gr.Radio(label="Translation Direction", choices = TRANSLATION_DIRECTION, value = "en -> lb") | |
| ] | |
| my_output = gr.Textbox(lines=5, label="Translation") | |
| def iwwersetz(source_text, model, direc): | |
| if model == "NLLB": | |
| translator = pipeline("translation", model=model_checkpoint_nllb) | |
| if direc == "en -> lb": | |
| translation = translator(source_text, src_lang="eng_Latn", tgt_lang="ltz_Latn") | |
| else: | |
| translation = translator(source_text, src_lang="ltz_Latn", tgt_lang="eng_Latn") | |
| elif model == "MarianNMT": | |
| if direc == "en -> lb": | |
| translator = pipeline("translation", model=model_checkpoint_marian_en) | |
| translation = translator(source_text) | |
| else: | |
| translator = pipeline("translation", model=model_checkpoint_marian_lb) | |
| translation = translator(source_text) | |
| elif model == "T5-mt5": | |
| translator = pipeline("translation", model=model_checkpoint_t5_mt5) | |
| translation = translator(source_text) | |
| else: | |
| translation = "Please select a Translation Model !" | |
| return translation | |
| demo=gr.Interface( | |
| fn=iwwersetz, | |
| inputs=my_inputs, | |
| outputs=my_output, | |
| title=my_title, | |
| description=my_description, | |
| article=my_article, | |
| examples=EXAMPLE, | |
| allow_flagging=False) | |
| demo.launch() |