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fix MultiHashEmbed example in documentation

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svlandeg 2020-10-09 14:11:06 +02:00
parent 4771a10503
commit 853edace37
2 changed files with 4 additions and 6 deletions
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2
spacy/ml/models/tok2vec.py
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@ -110,7 +110,7 @@ def MultiHashEmbed(
The features used can 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
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
(i.e. it's not updated).

8
website/docs/usage/embeddings-transformers.md
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@ -516,16 +516,14 @@ Many neural network models are able to use word vector tables as additional
features, which sometimes results in significant improvements in accuracy.
spaCy's built-in embedding layer,
[MultiHashEmbed](/api/architectures#MultiHashEmbed), can be configured to use
word vector tables using the `also_use_static_vectors` flag. This setting is
also available on the [MultiHashEmbedCNN](/api/architectures#MultiHashEmbedCNN)
layer, which builds the default token-to-vector encoding architecture.
word vector tables using the `include_static_vectors` flag.
```ini
[tagger.model.tok2vec.embed]
@architectures = "spacy.MultiHashEmbed.v1"
width = 128
rows = 7000
also_embed_subwords = true
attrs = ["NORM", "PREFIX", "SUFFIX", "SHAPE"]
rows = [7000, 3500, 3500, 3500]
also_use_static_vectors = true
```