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@ -377,7 +377,8 @@ A **model architecture** is a function that wires up a Thinc
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component or as a layer of a larger network. You can use Thinc as a thin
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[wrapper around frameworks](https://thinc.ai/docs/usage-frameworks) such as
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PyTorch, TensorFlow or MXNet, or you can implement your logic in Thinc
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[directly](https://thinc.ai/docs/usage-models).
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[directly](https://thinc.ai/docs/usage-models). For more details and examples,
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see the usage guide on [layers and architectures](/usage/layers-architectures).
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spaCy's built-in components will never construct their `Model` instances
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themselves, so you won't have to subclass the component to change its model
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@ -395,8 +396,6 @@ different tasks. For example:
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| [TransitionBasedParser](/api/architectures#TransitionBasedParser) | Build a [transition-based parser](https://explosion.ai/blog/parsing-english-in-python) model used in the default [`EntityRecognizer`](/api/entityrecognizer) and [`DependencyParser`](/api/dependencyparser). ~~Model[List[Docs], List[List[Floats2d]]]~~ |
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| [TextCatEnsemble](/api/architectures#TextCatEnsemble) | Stacked ensemble of a bag-of-words model and a neural network model with an internal CNN embedding layer. Used in the default [`TextCategorizer`](/api/textcategorizer). ~~Model[List[Doc], Floats2d]~~ |
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<!-- TODO: link to not yet existing usage page on custom architectures etc. -->
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### Metrics, training output and weighted scores {#metrics}
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When you train a model using the [`spacy train`](/api/cli#train) command, you'll
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@ -474,11 +473,9 @@ Each custom function can have any numbers of arguments that are passed in via
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the [config](#config), just the built-in functions. If your function defines
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**default argument values**, spaCy is able to auto-fill your config when you run
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[`init fill-config`](/api/cli#init-fill-config). If you want to make sure that a
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given parameter is always explicitely set in the config, avoid setting a default
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given parameter is always explicitly set in the config, avoid setting a default
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value for it.
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<!-- TODO: possibly link to new (not yet created) page on creating models ? -->
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### Training with custom code {#custom-code}
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> #### Example
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