se:
        lang = preproc.lang
    wv_url = (
        &#34;https://dl.fbaipublicfiles.com/fasttext/vectors-crawl/cc.%s.300.vec.gz&#34;
        % (lang.split(&#34;-&#34;)[0])
    )
    if verbose:
        print(&#34;word vectors will be loaded from: %s&#34; % (wv_url))

    # setup pre-trained word embeddings
    embed_size = 300
    U.vprint(&#34;processing pretrained word vectors...&#34;, verbose=verbose)
    embeddings_index = tpp.load_wv(wv_path_or_url=wv_url, verbose=verbose)
    word_index = tokenizer