How to use GloVe word embedding for non-English text

Question

I am trying to run a GloVe word embedding on a Bengali news dataset. Now the original GloVe source doesn't have any supported language other than English but I found this which has word vectors pretrained for 30 non-English languages.

I am running this notebook on text classification using GloVe embeddings. My question is

1. Can I use the pre-trained Bengali word vectors with my custom Bengali dataset, and run on this model?

2. this pretrained Bengali word vector is in tsv format. Using the following code I cannot seem to parse it into word-vector lists.

    embeddings_index = {}
    f = open(root_path + 'bn.tsv')
    for line in f:
        values = line.split('\t')
        word = values[1] ## The first entry is the word
        coefs = np.asarray(values[1:], dtype='float32') ## These are the vecotrs representing the embedding for the word
        embeddings_index[word] = coefs
    f.close()
   
    print('GloVe data loaded')
   

and I get the error

---------------------------------------------------------------------------
    ValueError                                Traceback (most recent call last)
    <ipython-input-39-3a4cb8d8dfb0> in <module>()
          4     values = line.split('\t')
          5     word = values[1] ## The first entry is the word
    ----> 6     coefs = np.asarray(values[1:], dtype='float32') ## These are the vecotrs representing the embedding for the word
          7     embeddings_index[word] = coefs
          8 f.close()

    /usr/local/lib/python3.6/dist-packages/numpy/core/_asarray.py in asarray(a, dtype, order)
         83 
         84     """
    ---> 85     return array(a, dtype, copy=False, order=order)
         86 
         87 

    ValueError: could not convert string to float: 'এবং'