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Update docs [ci skip]

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Ines Montani 2020-09-03 10:10:13 +02:00
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@ -377,7 +377,8 @@ A **model architecture** is a function that wires up a Thinc
component or as a layer of a larger network. You can use Thinc as a thin component or as a layer of a larger network. You can use Thinc as a thin
[wrapper around frameworks](https://thinc.ai/docs/usage-frameworks) such as [wrapper around frameworks](https://thinc.ai/docs/usage-frameworks) such as
PyTorch, TensorFlow or MXNet, or you can implement your logic in Thinc PyTorch, TensorFlow or MXNet, or you can implement your logic in Thinc
[directly](https://thinc.ai/docs/usage-models). [directly](https://thinc.ai/docs/usage-models). For more details and examples,
see the usage guide on [layers and architectures](/usage/layers-architectures).
spaCy's built-in components will never construct their `Model` instances spaCy's built-in components will never construct their `Model` instances
themselves, so you won't have to subclass the component to change its model themselves, so you won't have to subclass the component to change its model
@ -395,8 +396,6 @@ different tasks. For example:
| [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]]]~~ | | [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]]]~~ |
| [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]~~ | | [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]~~ |
<!-- TODO: link to not yet existing usage page on custom architectures etc. -->
### Metrics, training output and weighted scores {#metrics} ### Metrics, training output and weighted scores {#metrics}
When you train a model using the [`spacy train`](/api/cli#train) command, you'll When you train a model using the [`spacy train`](/api/cli#train) command, you'll
@ -474,11 +473,9 @@ Each custom function can have any numbers of arguments that are passed in via
the [config](#config), just the built-in functions. If your function defines the [config](#config), just the built-in functions. If your function defines
**default argument values**, spaCy is able to auto-fill your config when you run **default argument values**, spaCy is able to auto-fill your config when you run
[`init fill-config`](/api/cli#init-fill-config). If you want to make sure that a [`init fill-config`](/api/cli#init-fill-config). If you want to make sure that a
given parameter is always explicitely set in the config, avoid setting a default given parameter is always explicitly set in the config, avoid setting a default
value for it. value for it.
<!-- TODO: possibly link to new (not yet created) page on creating models ? -->
### Training with custom code {#custom-code} ### Training with custom code {#custom-code}
> #### Example > #### Example