Kannada_model

from transformers import TFAutoModelForSeq2SeqLM, AutoTokenizer
from transformers import pipeline

# Load the saved model and tokenizer
loaded_model = TFAutoModelForSeq2SeqLM.from_pretrained("ananya03/Kannada_model")
loaded_tokenizer = AutoTokenizer.from_pretrained("ananya03/Kannada_model")

# Step 9: Translate New Sentences
def translate_text(text):
    input_text = ">>kan<< " + text
    inputs = loaded_tokenizer(input_text, return_tensors="tf", padding=True, truncation=True)
    outputs = loaded_model.generate(inputs["input_ids"], num_beams=5, max_length=128, early_stopping=True)
    translated_text = loaded_tokenizer.decode(outputs[0], skip_special_tokens=True)
    return translated_text

# Example usage
english_text = "Good morning"
translated_text=translate_text(english_text)
print("Translated text:", translated_text)