Top2Vec
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ddangelov
Top2Vec learns jointly embedded topic, document and word vectors.
Hi Dimo, 'pip install top2vec' fails on Python 3.11 since dependency numba currently does not support 3.11. Do you know away around this issue, save waiting for numba to become...
On MacOS 13.3.1 with Python 3.9.16. When I run `pip3 install "top2vec[sentence_encoders]"`, pip installs top2vec-1.0.11. This version of top2vec doesn't appear to support `embedding_model` as a param: ``` pip3 install...
Could you please tell me how to get the topic size and topic number of the reduced hierarchical model?
Hi I'd like to know how to reduce the number of topics. Is there any function in top2vec that I can use?
I am using top2vec on a 2 processors windows 10 machine with 40 cores. I am running it with workers set to 36, but it is only using one processor....
Hi, I find that kernel is restarting when the model is finding dense topics. I face this issue when I use pre-trained BERT embedding and large dataset (7GB). Computing resources:...
This is not an issue but rather a question/feature request. Could Top2Vec be used to load an existing data with computed embedding vector for further analyses? I could not find...
Here is my topic_words outputs : 0 Words: ['and' 'the' 'in' 'to' 'of' 'games' 'or' 'first' 'game' 'that' 'by' 'at' 'is' 'released' 'with' 'as' 'its' 'was' 'from' 'developed' 'for' 'it'...
Hey, this is an amazing project to work with. I was wondering is there any way to extract topics from newly added document in inference. Thanks in advance.
Given a text corpus (German language), I get the following error with the code shown below: ` raise ValueError(f"A min_count of {min_count} results in " ValueError: A min_count of 50...
