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Remove hyphen from the curated-transformers.mdx
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@ -489,7 +489,7 @@ See the [usage documentation](/usage/embeddings-transformers#transformers) for
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how to integrate the architectures into your training config.
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how to integrate the architectures into your training config.
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When loading the model
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When loading the model
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[from the Hugging Face Hub](/api/curated-transformer#hf_trfencoder_loader), the
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[from the Hugging Face Hub](/api/curatedtransformer#hf_trfencoder_loader), the
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model config's parameters must be same as the hyperparameters used by the
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model config's parameters must be same as the hyperparameters used by the
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pre-trained model. The
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pre-trained model. The
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[`init fill-curated-transformer`](/api/cli#init-fill-curated-transformer) CLI
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[`init fill-curated-transformer`](/api/cli#init-fill-curated-transformer) CLI
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@ -188,7 +188,7 @@ $ python -m spacy init fill-config [base_path] [output_file] [--diff]
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### init fill-curated-transformer {id="init-fill-curated-transformer",version="3.7",tag="command"}
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### init fill-curated-transformer {id="init-fill-curated-transformer",version="3.7",tag="command"}
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Auto-fill the Hugging Face model hyperpameters and loader parameters of a
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Auto-fill the Hugging Face model hyperpameters and loader parameters of a
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[Curated Transformer](/api/curated-transformer) pipeline component in a
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[Curated Transformer](/api/curatedtransformer) pipeline component in a
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[.cfg file](/usage/training#config). The name and revision of the Hugging Face
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[.cfg file](/usage/training#config). The name and revision of the Hugging Face
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can either be passed as command-line arguments or read from the
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can either be passed as command-line arguments or read from the
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`initialize.components.transformer.encoder_loader` config section.
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`initialize.components.transformer.encoder_loader` config section.
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@ -224,8 +224,8 @@ modifying them.
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## CuratedTransformer.set_annotations {id="set_annotations",tag="method"}
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## CuratedTransformer.set_annotations {id="set_annotations",tag="method"}
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Assign the extracted features to the `Doc` objects. By default, the
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Assign the extracted features to the `Doc` objects. By default, the
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[`DocTransformerOutput`](/api/curated-transformer#doctransformeroutput) object
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[`DocTransformerOutput`](/api/curatedtransformer#doctransformeroutput) object is
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is written to the [`Doc._.trf_data`](#assigned-attributes) attribute. Your
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written to the [`Doc._.trf_data`](#assigned-attributes) attribute. Your
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`set_extra_annotations` callback is then called, if provided.
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`set_extra_annotations` callback is then called, if provided.
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> #### Example
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> #### Example
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