Initial version

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+model.sqlite filter=lfs diff=lfs merge=lfs -text
+vocab.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+tags:
+- sentence-similarity
+inference: false
+license: cc-by-sa-3.0
+language: english
+library_name: staticvectors
+---
+
+# FastText StaticVectors model
+
+This model is an export of these [FastText English Vectors](https://fasttext.cc/docs/en/english-vectors.html) (_wiki-news-300d-1M-subword.vec.zip_) for [`staticvectors`](https://github.com/neuml/staticvectors). `staticvectors` enables running inference Python with NumPy, helping it maintain solid runtime performance.
+
+## Usage with StaticVectors
+
+```python
+from staticvectors import StaticVectors
+
+model = StaticVectors("neuml/fasttext")
+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/fasttext/model.sqlite")
+model.embeddings(["word"])
+```

config.json

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+{
+  "model_type": "staticvectors",
+  "storage": "safetensors",
+  "format": "text",
+  "source": "wiki-news-300d-1M-subword.vec",
+  "total": 999994,
+  "dim": 300
+}

model.safetensors

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+size 1199992888

model.sqlite

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vocab.json

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