app.py

import gradio as gr
from transformers import T5ForConditionalGeneration, T5Tokenizer


model_name = 'jbochi/madlad400-3b-mt'
model = T5ForConditionalGeneration.from_pretrained(model_name, device_map="auto")
tokenizer = T5Tokenizer.from_pretrained(model_name)

def translate_to_russian(input_text):
    full_input_text = "<2ru>" + input_text  
    input_ids = tokenizer(full_input_text, return_tensors="pt").input_ids.to(model.device)

    outputs = model.generate(
        input_ids=input_ids,
        max_length=256,  
        num_beams=3,
        no_repeat_ngram_size=2,  
        length_penalty=1.2  
    )

    translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return translated_text

# Define Gradio interface
iface = gr.Interface(
    fn=translate_to_russian,
    inputs=[gr.Textbox(lines=10, placeholder="Enter text to translate")],
    outputs="textbox",
    title="Translate to Russian",
    description="Enter text in English and get the Russian translation.",
)

# Launch the interface
iface.launch(debug=True)