app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
import torch

model_checkpoint = "japanese-denim/m2m-finetuned-naga-to-eng"
model = AutoModelForSeq2SeqLM.from_pretrained(model_checkpoint)
tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)

def translate(text):
    translation_pipeline = pipeline("translation",
                                    model=model,
                                    tokenizer = tokenizer,
                                    src_lang='en',
                                    tgt_lang='en')

    result = translation_pipeline(text)
    return result[0]['translation_text']
    


gr.Interface(
    translate,
    [
        gr.components.Textbox(label="input", placeholder = "Enter Nagamese sentence here")
    ],
    ["text"],
).launch()