from transformers import AutoProcessor, SeamlessM4Tv2Model

processor = AutoProcessor.from_pretrained("facebook/seamless-m4t-v2-large")
model = SeamlessM4Tv2Model.from_pretrained("facebook/seamless-m4t-v2-large")

def translator(subtitle_line: str, target_language: str) -> str:
    # Ensure the model and processor are loaded to the GPU
    model.to('cuda')
    # Move input tensors to GPU
    text_inputs = processor(text=subtitle_line, src_lang="eng", return_tensors="pt")
    text_inputs = {key: value.to('cuda') for key, value in text_inputs.items()}
    # Generate output tokens on GPU
    output_tokens = model.generate(**text_inputs, tgt_lang=target_language, num_beams=5, generate_speech=False)
    # Decode the result
    return processor.decode(output_tokens[0].tolist()[0], skip_special_tokens=True)