how to do vector arithmetic? #160

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1. rmitsch

   added

   usageGeneral usageGeneral usage

   on Oct 13, 2023
2. rmitsch commented on Oct 13, 2023

   

   rmitsch

   on Oct 13, 2023

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   You can obtain the vectors like this (see example in the readme):

   import spacy
   
   nlp = spacy.load("en_core_web_sm")
   s2v = nlp.add_pipe("sense2vec")
   s2v.from_disk("/path/to/s2v_reddit_2015_md")
   
   doc = nlp("A sentence about natural language processing.")
   vector = doc[3:6]._.s2v_vec

   You can then use e. g. numpy to do whatever vector arithmetic on the embeddings you obtained.
3. sleepandpancakes commented on Oct 14, 2023

   

   sleepandpancakes

   on Oct 14, 2023

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   thank you. is there a way to take an arbitrary vector and find the closest corresponding word in the vocab? i'm still having a bit of trouble understanding how i would do this
4. rmitsch commented on Oct 16, 2023

   

   rmitsch

   on Oct 16, 2023

   Last edited by rmitsch

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   What you're looking for is a nearest neighbor search. sense2vec doesn't expose this in the public API, but there are a lot of tools for this - sorted by complexity/overhead/capabilities from low to high:

   • In-memory solutions like scikit-learn's KNN implementation
   • File-based solutions like annoy or FAISS
   • Vector DBs like Weaviate, Pinecone, etc.
5. sleepandpancakes commented on Oct 23, 2023

   

   sleepandpancakes

   on Oct 23, 2023

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   thank you again