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Remove hyphen from the curated-transformers.mdx filename

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website/docs/api/architectures.mdx
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@ -489,7 +489,7 @@ See the [usage documentation](/usage/embeddings-transformers#transformers) for
how to integrate the architectures into your training config. how to integrate the architectures into your training config.
When loading the model When loading the model
[from the Hugging Face Hub](/api/curated-transformer#hf_trfencoder_loader), the [from the Hugging Face Hub](/api/curatedtransformer#hf_trfencoder_loader), the
model config's parameters must be same as the hyperparameters used by the model config's parameters must be same as the hyperparameters used by the
pre-trained model. The pre-trained model. The
[`init fill-curated-transformer`](/api/cli#init-fill-curated-transformer) CLI [`init fill-curated-transformer`](/api/cli#init-fill-curated-transformer) CLI

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website/docs/api/cli.mdx
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@ -188,7 +188,7 @@ $ python -m spacy init fill-config [base_path] [output_file] [--diff]
### init fill-curated-transformer {id="init-fill-curated-transformer",version="3.7",tag="command"} ### init fill-curated-transformer {id="init-fill-curated-transformer",version="3.7",tag="command"}
Auto-fill the Hugging Face model hyperpameters and loader parameters of a Auto-fill the Hugging Face model hyperpameters and loader parameters of a
[Curated Transformer](/api/curated-transformer) pipeline component in a [Curated Transformer](/api/curatedtransformer) pipeline component in a
[.cfg file](/usage/training#config). The name and revision of the Hugging Face [.cfg file](/usage/training#config). The name and revision of the Hugging Face
can either be passed as command-line arguments or read from the can either be passed as command-line arguments or read from the
`initialize.components.transformer.encoder_loader` config section. `initialize.components.transformer.encoder_loader` config section.

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website/docs/api/curated-transformer.mdx → website/docs/api/curatedtransformer.mdx
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@ -224,8 +224,8 @@ modifying them.
## CuratedTransformer.set_annotations {id="set_annotations",tag="method"} ## CuratedTransformer.set_annotations {id="set_annotations",tag="method"}
Assign the extracted features to the `Doc` objects. By default, the Assign the extracted features to the `Doc` objects. By default, the
[`DocTransformerOutput`](/api/curated-transformer#doctransformeroutput) object [`DocTransformerOutput`](/api/curatedtransformer#doctransformeroutput) object is
is written to the [`Doc._.trf_data`](#assigned-attributes) attribute. Your written to the [`Doc._.trf_data`](#assigned-attributes) attribute. Your
`set_extra_annotations` callback is then called, if provided. `set_extra_annotations` callback is then called, if provided.
> #### Example > #### Example