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Fix formatting [ci skip]
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@ -166,10 +166,9 @@ cosines are calculated in minibatches, to reduce memory usage.
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## Vocab.get_vector {#get_vector tag="method" new="2"}
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Retrieve a vector for a word in the vocabulary. Words can be looked up by string
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or hash value. If no vectors data is loaded, a `ValueError` is raised.
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If `minn` is defined, then the resulting vector uses Fasttext's
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subword features by average over ngrams of `orth`. (Introduced in spaCy `v2.1`)
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or hash value. If no vectors data is loaded, a `ValueError` is raised. If `minn`
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is defined, then the resulting vector uses [FastText](https://fasttext.cc/)'s
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subword features by average over ngrams of `orth` (introduced in spaCy `v2.1`).
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> #### Example
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>
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@ -178,12 +177,12 @@ subword features by average over ngrams of `orth`. (Introduced in spaCy `v2.1`)
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> nlp.vocab.get_vector("apple", minn=1, maxn=5)
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> ```
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| Name | Type | Description |
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| ----------- | ---------------------------------------- | ---------------------------------------------------------------------------------------------- |
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| `orth` | int / unicode | The hash value of a word, or its unicode string. |
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| `minn` | int | Minimum n-gram length used for Fasttext's ngram computation. Defaults to the length of `orth`. |
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| `maxn` | int | Maximum n-gram length used for Fasttext's ngram computation. Defaults to the length of `orth`. |
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| **RETURNS** | `numpy.ndarray[ndim=1, dtype='float32']` | A word vector. Size and shape are determined by the `Vocab.vectors` instance. |
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| Name | Type | Description |
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| ----------------------------------- | ---------------------------------------- | ---------------------------------------------------------------------------------------------- |
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| `orth` | int / unicode | The hash value of a word, or its unicode string. |
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| `minn` <Tag variant="new">2.1</Tag> | int | Minimum n-gram length used for FastText's ngram computation. Defaults to the length of `orth`. |
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| `maxn` <Tag variant="new">2.1</Tag> | int | Maximum n-gram length used for FastText's ngram computation. Defaults to the length of `orth`. |
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| **RETURNS** | `numpy.ndarray[ndim=1, dtype='float32']` | A word vector. Size and shape are determined by the `Vocab.vectors` instance. |
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## Vocab.set_vector {#set_vector tag="method" new="2"}
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