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import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
import torch
LANGS = ["kin_Latn","eng_Latn"]
TASK = "translation"
# CKPT = "DigitalUmuganda/Finetuned-NLLB"
# MODELS = ["facebook/nllb-200-distilled-600M","DigitalUmuganda/Finetuned-NLLB"]
# model = AutoModelForSeq2SeqLM.from_pretrained(CKPT)
# tokenizer = AutoTokenizer.from_pretrained(CKPT)
device = 0 if torch.cuda.is_available() else -1
general_model = AutoModelForSeq2SeqLM.from_pretrained("mbazaNLP/Nllb_finetuned_general_en_kin")
#education_model = AutoModelForSeq2SeqLM.from_pretrained("mbazaNLP/Nllb_finetuned_education_en_kin")
#tourism_model = AutoModelForSeq2SeqLM.from_pretrained("mbazaNLP/Nllb_finetuned_tourism_en_kin")
#MODELS = {"General model":general_model_model,"Education model":education_model,"Tourism model":tourism_model}
#MODELS = {"Education model":education_model,"Tourism model":tourism_model}
tokenizer = AutoTokenizer.from_pretrained("mbazaNLP/Nllb_finetuned_general_en_kin")
# def translate(text, src_lang, tgt_lang, max_length=400):
TASK = "translation"
device = 0 if torch.cuda.is_available() else -1
def translate(text, source_lang, target_lang, max_length=400):
"""
Translate text from source language to target language
"""
# src_lang = choose_language(source_lang)
# tgt_lang= choose_language(target_lang)
# if src_lang==None:
# return "Error: the source langage is incorrect"
# elif tgt_lang==None:
# return "Error: the target language is incorrect"
translation_pipeline = pipeline(TASK,
model=general_model,
tokenizer=tokenizer,
src_lang=source_lang,
tgt_lang=target_lang,
max_length=max_length,
device=device)
result = translation_pipeline(text)
return result[0]['translation_text']
gradio_ui= gr.Interface(
fn=translate,
title="NLLB-General EN-KIN Translation Demo",
inputs= [
gr.components.Textbox(label="Text"),
gr.components.Dropdown(label="Source Language", choices=LANGS),
gr.components.Dropdown(label="Target Language", choices=LANGS),
# gr.components.Slider(8, 400, value=400, step=8, label="Max Length")
],
outputs=gr.outputs.Textbox(label="Translated text")
)
gradio_ui.launch()
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