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@ -330,9 +330,9 @@ See the [`Transformer`](/api/transformer) API reference and
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> ```
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| Registry name | Description |
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| ------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| ----------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| [`span_getters`](/api/transformer#span_getters) | Registry for functions that take a batch of `Doc` objects and return a list of `Span` objects to process by the transformer, e.g. sentences. |
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| [`annotation_setters`](/api/transformers#annotation_setters) | Registry for functions that create annotation setters. Annotation setters are functions that take a batch of `Doc` objects and a [`FullTransformerBatch`](/api/transformer#fulltransformerbatch) and can set additional annotations on the `Doc`. |
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| [`annotation_setters`](/api/transformer#annotation_setters) | Registry for functions that create annotation setters. Annotation setters are functions that take a batch of `Doc` objects and a [`FullTransformerBatch`](/api/transformer#fulltransformerbatch) and can set additional annotations on the `Doc`. |
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## Training data loaders and batchers {#loaders-batchers new="3"}
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@ -68,6 +68,10 @@ const QuickstartTraining = ({ id, title, download = 'config.cfg' }) => {
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id: code,
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title: name,
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}))
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const recommendedTrf = Object.assign(
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{},
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...langs.map(({ code }) => ({ [code]: { sm: 'TODO', lg: 'TODO' } }))
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)
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return (
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<Quickstart
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download={download}
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@ -85,14 +89,20 @@ const QuickstartTraining = ({ id, title, download = 'config.cfg' }) => {
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<span>[components]</span>
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<br />
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<span>[components.transformer]</span>
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<QS optimize="efficiency">name = "{MODELS_SMALL[lang]}"</QS>
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<QS optimize="accuracy">name = "{MODELS_LARGE[lang]}"</QS>
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<QS optimize="efficiency">name = "{recommendedTrf[lang].sm}"</QS>
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<QS optimize="accuracy">name = "{recommendedTrf[lang].lg}"</QS>
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{!!pipeline.length && <br />}
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{pipeline.map((pipe, i) => (
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<>
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{i !== 0 && <br />}
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<span>[components.{pipe}]</span>
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<span>factory = "{pipe}"</span>
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<QS config="independent">
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<br />
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[components.parser.model.tok2vec]
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<br />
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@architectures = "spacy.Tok2Vec.v1"
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</QS>
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</>
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))}
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</Quickstart>
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