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from transformers import MBartForConditionalGeneration, MBart50Tokenizer
import gradio as gr
# Load mBART model and tokenizer for multilingual translation
model_name = 'facebook/mbart-large-50-many-to-one-mmt' # mBART 50 for many-to-one translation (many languages to English)
tokenizer = MBart50Tokenizer.from_pretrained(model_name)
model = MBartForConditionalGeneration.from_pretrained(model_name)
# Set the source language code (Tamil)
tokenizer.src_lang = "ta_IN" # Tamil language code
# Function for translation
def translate(text):
inputs = tokenizer(text, return_tensors="pt")
generated_tokens = model.generate(**inputs)
translated_text = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]
return translated_text
# Launch a Gradio interface
interface = gr.Interface(fn=translate, inputs="text", outputs="text", title="Tamil to English Translator")
interface.launch()
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