          +cell Assign document labels.
  
  p
      |  The processing pipeline always #[strong depends on the statistical model]
      |  and its capabilities. For example, a pipeline can only include an entity
      |  recognizer component if the model includes data to make predictions of
      |  entity labels. This is why each model will specify the pipeline to use
 
</s> remove     "pipeline": ["tensorizer", "tagger", "parser", "ner"]
 </s> add     "pipeline": ["tagger", "parser", "ner"] </s> remove     | ... the model tells spaCy to use the language #[code "en"] and the pipeline
    |  #[code.u-break ["tensorizer", "tagger", "parser", "ner"]]. spaCy will
    |  then initialise #[code spacy.lang.en.English], and create each pipeline
 </s> add     | ... the model tells spaCy to use the language #[code "en"] and the
    |  pipeline #[code.u-break ["tagger", "parser", "ner"]]. spaCy will then
    |  initialise #[code spacy.lang.en.English], and create each pipeline </s> remove     |  require certain modifications on the #[code Doc] to process it. For
    |  example, the default pipeline first applies the tensorizer, which
    |  pre-processes the doc and encodes its internal
 </s> add     |  require certain modifications on the #[code Doc] to process it. As the
    |  processing pipeline is applied, spaCy encodes the document's internal </s> remove     |  document. This step is similar to the #[+api("tensorizer") #[code Tensorizer]]
    |  component, but the #[code TextCategorizer] uses its own CNN model, to
 </s> add     |  document. The #[code TextCategorizer] uses its own CNN model, to </s> remove     |  required for the next component, the tagger, to make predictions of the
 </s> add     |  required for the first component, the tagger, to make predictions of the
    +row("divider")
        +cell #[strong &period;&period;&period;]
        +cell #[+a("/usage/processing-pipelines#custom-components") custom components]
        +cell #[code Doc._.xxx], #[code Token._.xxx], #[code Span._.xxx]
        +cell Assign custom attributes, methods or properties.

          +cell Assign document labels.
  
    +row("divider")
        +cell #[strong &period;&period;&period;]
        +cell #[+a("/usage/processing-pipelines#custom-components") custom components]
        +cell #[code Doc._.xxx], #[code Token._.xxx], #[code Span._.xxx]
        +cell Assign custom attributes, methods or properties.

  p
      |  The processing pipeline always #[strong depends on the statistical model]
      |  and its capabilities. For example, a pipeline can only include an entity
      |  recognizer component if the model includes data to make predictions of
      |  entity labels. This is why each model will specify the pipeline to use
keep add keep keep keep keep keep
 Don't document the tensorizer for now 
website/usage/_spacy-101/_pipelines.jade