def METHOD_NAME(audio, model):
    """
    audio: n_sounds x n_samples of mono audio in the range [-1, 1]. All sounds in a batch will be padded/trimmed to the same length.
    model: Loaded Model.
    Returns:
    embedding: A float32 Tensor with shape (n_sounds, n_timestamps, model.timestamp_embedding_size).
    timestamps: A float32 Tensor with shape (`n_sounds, n_timestamps). Centered timestamps in milliseconds corresponding to each embedding in the output.
    """
    model.eval()
    with torch.no_grad():
        return model.get_timestamp_embeddings(audio)