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ETM - Possibility of using KeyedVectors input for pre-trained W2V embeddings

See original GitHub issue

OCTIS version: 1.9.0
Python version: 3.7.6
Operating System: Ubuntu 20.04 LTS

Description

Hi, this is more of a question than anything else. I’ve seen that for ETM model training, we must pass an embeddings path corresponding to a “pickled” file. However, I need to execute ETM with rather large embeddings. There’s any intent on implementing a gensim.models.KeyedVectors based (or something like that) embeddings input for this model? I’ve implemented something like that for an etm package of mine, but yours’ has all I need to execute model optimization. Would a PR on this matter be accepted?

Anyway, cheers for the nice work, this package is really great!

What I Did

Gave a look at here.

Issue Analytics

State:
Created 2 years ago
Comments:8 (2 by maintainers)

Top GitHub Comments

3reactions

silviatticommented, Nov 21, 2021

Hi, I merged the PR on the branch dev_etm. Now I’m going to fix another issue and make the new release. It should be available in the next few hours. Thank you for your patience 😃

1reaction

cayalukecommented, Nov 9, 2021

@lffloyd Thank you for your response. It is much appreciated.

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