diff --git a/website/docs/api/dependencyparser.md b/website/docs/api/dependencyparser.md index ed5e8bdb2..5bd2ea8ad 100644 --- a/website/docs/api/dependencyparser.md +++ b/website/docs/api/dependencyparser.md @@ -297,7 +297,8 @@ Add a new label to the pipe. Note that you don't have to call this method if you provide a **representative data sample** to the [`begin_training`](#begin_training) method. In this case, all labels found in the sample will be automatically added to the model, and the output dimension -will be [inferred](/usage/layers-architectures#shape-inference) automatically. +will be [inferred](/usage/layers-architectures#thinc-shape-inference) +automatically. > #### Example > diff --git a/website/docs/api/entityrecognizer.md b/website/docs/api/entityrecognizer.md index fc6904824..9189fe763 100644 --- a/website/docs/api/entityrecognizer.md +++ b/website/docs/api/entityrecognizer.md @@ -285,7 +285,8 @@ Add a new label to the pipe. Note that you don't have to call this method if you provide a **representative data sample** to the [`begin_training`](#begin_training) method. In this case, all labels found in the sample will be automatically added to the model, and the output dimension -will be [inferred](/usage/layers-architectures#shape-inference) automatically. +will be [inferred](/usage/layers-architectures#thinc-shape-inference) +automatically. > #### Example > diff --git a/website/docs/api/language.md b/website/docs/api/language.md index 9c9ccb6cf..530f7740d 100644 --- a/website/docs/api/language.md +++ b/website/docs/api/language.md @@ -205,8 +205,8 @@ examples can either be the full training data or a representative sample. They are used to **initialize the models** of trainable pipeline components and are passed each component's [`begin_training`](/api/pipe#begin_training) method, if available. Initialization includes validating the network, -[inferring missing shapes](/usage/layers-architectures#shape-inference) and -setting up the label scheme based on the data. +[inferring missing shapes](/usage/layers-architectures#thinc-shape-inference) +and setting up the label scheme based on the data. If no `get_examples` function is provided when calling `nlp.begin_training`, the pipeline components will be initialized with generic data. In this case, it is diff --git a/website/docs/api/morphologizer.md b/website/docs/api/morphologizer.md index c83d3d9fd..c4787c050 100644 --- a/website/docs/api/morphologizer.md +++ b/website/docs/api/morphologizer.md @@ -263,7 +263,8 @@ already been fully [initialized](#begin_training). Note that you don't have to call this method if you provide a **representative data sample** to the [`begin_training`](#begin_training) method. In this case, all labels found in the sample will be automatically added to the model, and the output dimension -will be [inferred](/usage/layers-architectures#shape-inference) automatically. +will be [inferred](/usage/layers-architectures#thinc-shape-inference) +automatically. > #### Example > diff --git a/website/docs/api/pipe.md b/website/docs/api/pipe.md index be1279553..ec4b0ff1b 100644 --- a/website/docs/api/pipe.md +++ b/website/docs/api/pipe.md @@ -317,7 +317,7 @@ Note that in general, you don't have to call `pipe.add_label` if you provide a representative data sample to the [`begin_training`](#begin_training) method. In this case, all labels found in the sample will be automatically added to the model, and the output dimension will be -[inferred](/usage/layers-architectures#shape-inference) automatically. +[inferred](/usage/layers-architectures#thinc-shape-inference) automatically. ## Pipe.is_resizable {#is_resizable tag="method"} diff --git a/website/docs/api/tagger.md b/website/docs/api/tagger.md index eceb28b19..06def58d5 100644 --- a/website/docs/api/tagger.md +++ b/website/docs/api/tagger.md @@ -293,8 +293,8 @@ set, or if the model has already been fully [initialized](#begin_training). Note that you don't have to call this method if you provide a **representative data sample** to the [`begin_training`](#begin_training) method. In this case, all labels found in the sample will be automatically added to the model, and the -output dimension will be [inferred](/usage/layers-architectures#shape-inference) -automatically. +output dimension will be +[inferred](/usage/layers-architectures#thinc-shape-inference) automatically. > #### Example > diff --git a/website/docs/api/textcategorizer.md b/website/docs/api/textcategorizer.md index 0d71655c6..b296c95ca 100644 --- a/website/docs/api/textcategorizer.md +++ b/website/docs/api/textcategorizer.md @@ -302,8 +302,8 @@ set, or if the model has already been fully [initialized](#begin_training). Note that you don't have to call this method if you provide a **representative data sample** to the [`begin_training`](#begin_training) method. In this case, all labels found in the sample will be automatically added to the model, and the -output dimension will be [inferred](/usage/layers-architectures#shape-inference) -automatically. +output dimension will be +[inferred](/usage/layers-architectures#thinc-shape-inference) automatically. > #### Example >