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import gradio as gr | |
from transformers import MarianMTModel, MarianTokenizer | |
import torch | |
# Load the model and tokenizer from the Hub | |
model_name = "Dddixyy/latin-italian-translatorV5" | |
tokenizer = MarianTokenizer.from_pretrained(model_name) | |
model = MarianMTModel.from_pretrained(model_name) | |
# Translation function | |
def translate_latin_to_italian(latin_text): | |
# Make the first letter lowercase if the input is not empty | |
if latin_text: | |
latin_text = latin_text[0].lower() + latin_text[1:] | |
inputs = tokenizer(latin_text, return_tensors="pt", padding=True, truncation=True) | |
with torch.no_grad(): | |
generated_ids = model.generate(inputs["input_ids"]) | |
translation = tokenizer.batch_decode(generated_ids, skip_special_tokens=True) | |
return translation[0] | |
# Define the Gradio interface | |
interface = gr.Interface( | |
fn=translate_latin_to_italian, | |
inputs="text", | |
outputs="text", | |
title="Latin to Italian Translator", | |
description="Translate Latin sentences to Italian using a fine-tuned MarianMT model.", | |
examples=[ | |
["Amor vincit omnia."], | |
["Veni, vidi, vici."], | |
["Carpe diem."], | |
["Alea iacta est."] | |
] | |
) | |
# Launch the app | |
if __name__ == "__main__": | |
interface.launch() |