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--- |
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tags: |
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- sentence-similarity |
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inference: false |
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license: apache-2.0 |
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language: en |
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library_name: staticvectors |
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base_model: |
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- NeuML/word2vec |
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--- |
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# Word2Vec StaticVectors model |
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This model is an export of these [Word2Vec Vectors](https://code.google.com/archive/p/word2vec/) for [`staticvectors`](https://github.com/neuml/staticvectors). `staticvectors` enables running inference in Python with NumPy. This helps it maintain solid runtime performance. |
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_This model is a quantized version of the base model. It's using 10x256 Product Quantization._ |
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## Usage with StaticVectors |
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```python |
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from staticvectors import StaticVectors |
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model = StaticVectors("neuml/word2vec-quantized") |
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model.embeddings(["word"]) |
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``` |
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Given that pre-trained embeddings models can get quite large, there is also a SQLite version that lazily loads vectors. |
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```python |
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from staticvectors import StaticVectors |
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model = StaticVectors("neuml/word2vec-quantized/model.sqlite") |
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model.embeddings(["word"]) |
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``` |
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