Initial version

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
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+model.sqlite filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+tags:
+- sentence-similarity
+inference: false
+license: apache-2.0
+language: en
+library_name: staticvectors
+base_model:
+- NeuML/word2vec
+---
+
+# Word2Vec StaticVectors model
+
+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.
+
+_This model is a quantized version of the base model. It's using 10x256 Product Quantization._
+
+## Usage with StaticVectors
+
+```python
+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.
+
+```python
+from staticvectors import StaticVectors
+
+model = StaticVectors("neuml/word2vec/model.sqlite")
+model.embeddings(["word"])
+```

config.json

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+{
+  "model_type": "staticvectors",
+  "storage": "safetensors",
+  "format": "text",
+  "source": "GoogleNews-vectors-negative300.txt",
+  "total": 3000000,
+  "dim": 300
+}

model.safetensors

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+size 30307440

vocab.json

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