  
          "Pipeline": {
              "Language": "language",
              "Pipe": "pipe",
              "Tensorizer": "tensorizer",
              "Tagger": "tagger",
              "DependencyParser": "dependencyparser",
              "EntityRecognizer": "entityrecognizer",
              "TextCategorizer": "textcategorizer",
              "Tokenizer": "tokenizer",
 
</s> remove     "tensorizer": {
        "title": "Tensorizer",
        "teaser": "Add a tensor with position-sensitive meaning representations to a document.",
        "tag": "class",
        "tag_new": 2,
        "source": "spacy/pipeline.pyx"
    },

 </s> add  </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     |  tensor is then
    |  summarized by concatenating max and mean pooling, and a multilayer
    |  perceptron is used to predict an output vector of length #[code nr_class],
    |  before a logistic activation is applied elementwise. The value of each
    |  output neuron is the probability that some class is present.
 </s> add     |  tensor is then summarized by concatenating max and mean pooling, and a
    |  multilayer perceptron is used to predict an output vector of length
    |  #[code nr_class], before a logistic activation is applied elementwise.
    |  The value of each output neuron is the probability that some class is
    |  present. </s> remove     nlp = English().from_disk('/model', disable=['tensorizer', 'ner'])
 </s> add     nlp = English().from_disk('/model', disable=['ner'])
  
          "Pipeline": {
              "Language": "language",
              "Pipe": "pipe",

              "Tagger": "tagger",
              "DependencyParser": "dependencyparser",
              "EntityRecognizer": "entityrecognizer",
              "TextCategorizer": "textcategorizer",
              "Tokenizer": "tokenizer",
keep keep keep keep replace keep keep keep keep keep
 Don't document the tensorizer for now 
website/api/_data.json