    def setup(self) -> None:
        """Load the model into memory to make running multiple predictions efficient"""
        os.environ["TRANSFORMERS_OFFLINE"] = "1"

        # Download weights if they don't exist
        if not os.path.exists(MODEL_CACHE):
            download_weights(MODEL_URL, MODEL_CACHE)
        
        # Load model and tokenizer
        self.model = AutoModelForCausalLM.from_pretrained(
            MODEL_CACHE,
            torch_dtype="auto",
            device_map="cuda:0",
            trust_remote_code=True,
        ).eval().cuda()

        self.tokenizer = AutoTokenizer.from_pretrained(
            MODEL_CACHE,
            trust_remote_code=True,
        )
Load the model into memory to make running multiple predictions efficient
demo/predict-vid.py