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Thanks for your work again!
In the paper the topic modeling of OBELICS is implemented using LDA, and I am wondering what is the specific LDA model was used, what setting was used to train the model, …
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Hi, first of all thanks for developing this clean and handy tool.
When I call `nlp.train_lda_model()` I get the following error:
```
ModuleNotFoundError: No module named 'gensim.models.lda'
`…
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python main.py --title HOZ --model HOZ --workers 12 --gpu-ids 0
python full_eval.py --title HOZ --model HOZ --results-json HOZ.json --gpu-ids 0
When I ran the above two codes for training and eval…
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Similarly to the previous issue: Build LDA models
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I am trying to follow tutorial at http://docs.bigartm.org/en/stable/tutorials/python_tutorial.html and run into some issues. Here is the sample code for training LDA model on wiki-enru dataset:
```…
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I have trained LDA model using Gensim, and now want to use topicwizard for visualization.
But even after following the Readme for using Gensim topic model case, it doesn't seem to work.
Note: I am…
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The current code in the tutorial for aggregating coherence at various numbers of topics is very memory intensive and can cause python to crash. This is because it aggregates all of the lda models in t…
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Results of unigram LDA model are usually hard to interpret so I am wondering that if you could improve the interpretability by using [a n-grams LDA model](https://people.cs.umass.edu/~mccallum/papers/…
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model_results = run_cgs_models_mallet(
cistopic_obj=cistopic_obj,
n_topics=n_topics,
n_cpu=n_cpu,
n_iter=n_iter,
random_state=random_state,
alpha…