How to visualize Gensim Word2vec Embeddings in Tensorboard Projector

Following gensim word2vec embedding tutorial, I have trained a simple word2vec model:

from gensim.test.utils import common_texts
from gensim.models import Word2Vec
model = Word2Vec(sentences=common_texts, size=100, window=5, min_count=1, workers=4)
model.save("/content/word2vec.model")

I would like to visualize it using the Embedding Projector in TensorBoard. There is another straightforward tutorial in gensim documentation. I did the following in Colab:

!python3 -m gensim.scripts.word2vec2tensor -i /content/word2vec.model -o /content/my_model

Traceback (most recent call last):
  File "/usr/lib/python3.7/runpy.py", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/usr/lib/python3.7/runpy.py", line 85, in _run_code
    exec(code, run_globals)
  File "/usr/local/lib/python3.7/dist-packages/gensim/scripts/word2vec2tensor.py", line 94, in <module>
    word2vec2tensor(args.input, args.output, args.binary)
  File "/usr/local/lib/python3.7/dist-packages/gensim/scripts/word2vec2tensor.py", line 68, in word2vec2tensor
    model = gensim.models.KeyedVectors.load_word2vec_format(word2vec_model_path, binary=binary)
  File "/usr/local/lib/python3.7/dist-packages/gensim/models/keyedvectors.py", line 1438, in load_word2vec_format
    limit=limit, datatype=datatype)
  File "/usr/local/lib/python3.7/dist-packages/gensim/models/utils_any2vec.py", line 172, in _load_word2vec_format
    header = utils.to_unicode(fin.readline(), encoding=encoding)
  File "/usr/local/lib/python3.7/dist-packages/gensim/utils.py", line 355, in any2unicode
    return unicode(text, encoding, errors=errors)

UnicodeDecodeError: 'utf-8' codec can't decode byte 0x80 in position 0: invalid start byte

Please note that I did check first this exact same question from 2018 - but the accepted answer no longer works as both in gensim and tensorflow have been updated so I considered it was worth asking again in Q4 2021.

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