app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

model_name = "Khadidja22/my_awesome_opus_books_model"

# Load the tokenizer and model
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

def translate(text):
    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512).input_ids
    outputs = model.generate(inputs, max_length=512, num_beams=5, early_stopping=True)
    translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return translated_text

# Create a Gradio interface
interface = gr.Interface(fn=translate, 
                         inputs=gr.Textbox(lines=2, placeholder="Enter English text to translate..."), 
                         outputs=gr.Textbox(), 
                         title="English to French Translation",
                         description="Translate English text to French using a fine-tuned model, start your sentence with translate English to French:")

# Launch the interface
interface.launch()