Word2Vec StaticVectors model

This model is an export of these Word2Vec Vectors for staticvectors. staticvectors enables running inference in Python with NumPy. This helps it maintain solid runtime performance.

Usage with StaticVectors

from staticvectors import StaticVectors

model = StaticVectors("neuml/word2vec")
model.embeddings(["word"])

Given that pre-trained embeddings models can get quite large, there is also a SQLite version that lazily loads vectors.

from staticvectors import StaticVectors

model = StaticVectors("neuml/word2vec/model.sqlite")
model.embeddings(["word"])
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Model size
900M params
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F32
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