    tokenizer = AutoTokenizer.from_pretrained(base_model, cache_dir=path_to_cache)
    model = AutoModelForCausalLM.from_pretrained(
        base_model, attn_implementation="sdpa", torch_dtype=torch.bfloat16, cache_dir=path_to_cache
    )
    model.gradient_checkpointing_enable()

        {"additional_special_tokens": [start_audio_token, end_audio_token]}
    )
    n_tokens = len(tokenizer)
    print("Not audio tokens:", n_tokens)
    start_audio_token_id = tokenizer(start_audio_token)["input_ids"][-1]
