Comments (1)
It seems other people, including myself, are also experiencing your issue of the topic/document embeddings not training properly. As for your other issue...
Take a look at these 2 links to Chris Moody's repository. He doesn't name it f_embed, but it is the same variable I believe.
https://github.com/cemoody/lda2vec/blob/master/examples/twenty_newsgroups/data/preprocess.py
https://github.com/cemoody/lda2vec/blob/master/lda2vec/corpus.py
In preprocess.py, we see he passes google news embeddings to a function to return the pretrained embeddings.
By googling 'GoogleNews-vectors-negative300.bin' you can find a place to download it.
from lda2vec-tf.
Related Issues (14)
- Infer the vector of a new document with the lda2vec model
- When I am using the code in jupyter notebook, the kernal is always getting stopped,why? ( I have changed the code slightly ,because it is giving a lot of errors.)
- get the embedding of a new document HOT 18
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- train lda2evc
- Import of module "projector" not working with Tensorflow 2
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- Model does not learn topic embeddings and document embedding.
- why is loss_nce NaN through out the training phase ? HOT 2
- Negative sampling HOT 1
- NameError: name 'w2i' is not defined HOT 1
- expected results
- Giving same representaion for every document. HOT 10
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from lda2vec-tf.