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MultiHashEmbed vector docs correction (#9918)

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Peter Baumgartner 2021-12-27 05:18:08 -05:00 committed by GitHub
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2 changed files with 4 additions and 4 deletions
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2
spacy/ml/models/tok2vec.py
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@ -123,7 +123,7 @@ def MultiHashEmbed(
attributes are NORM, PREFIX, SUFFIX and SHAPE. This lets the model take into
account some subword information, without constructing a fully character-based
representation. If pretrained vectors are available, they can be included in
the representation as well, with the vectors table will be kept static
the representation as well, with the vectors table kept static
(i.e. it's not updated).
The `width` parameter specifies the output width of the layer and the widths

6
website/docs/api/architectures.md
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@ -158,7 +158,7 @@ be configured with the `attrs` argument. The suggested attributes are `NORM`,
`PREFIX`, `SUFFIX` and `SHAPE`. This lets the model take into account some
subword information, without construction a fully character-based
representation. If pretrained vectors are available, they can be included in the
representation as well, with the vectors table will be kept static (i.e. it's
representation as well, with the vectors table kept static (i.e. it's
not updated).
| Name | Description |
@ -296,7 +296,7 @@ learned linear projection to control the dimensionality. Unknown tokens are
mapped to a zero vector. See the documentation on
[static vectors](/usage/embeddings-transformers#static-vectors) for details.
| Name |  Description |
| Name | Description |
| ----------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `nO` | The output width of the layer, after the linear projection. ~~Optional[int]~~ |
| `nM` | The width of the static vectors. ~~Optional[int]~~ |
@ -318,7 +318,7 @@ mapped to a zero vector. See the documentation on
Extract arrays of input features from [`Doc`](/api/doc) objects. Expects a list
of feature names to extract, which should refer to token attributes.
| Name |  Description |
| Name | Description |
| ----------- | ------------------------------------------------------------------------ |
| `columns` | The token attributes to extract. ~~List[Union[int, str]]~~ |
| **CREATES** | The created feature extraction layer. ~~Model[List[Doc], List[Ints2d]]~~ |