          |  #[code Span].
  
      +github("spacy", "examples/pipeline/custom_attr_methods.py")
  
  +section("training")
      +h(3, "training-ner") Training spaCy's Named Entity Recognizer
  
      p
          |  This example shows how to update spaCy's entity recognizer
          |  with your own examples, starting off with an existing, pre-trained
 
</s> remove Example of multi-processing with joblib. Here, we're exporting
 </s> add Example of multi-processing with Joblib. Here, we're exporting </s> remove each "sentence" on a newline, and spaces between tokens.
 </s> add each "sentence" on a newline, and spaces between tokens. Data is loaded from
the IMDB movie reviews dataset and will be loaded automatically via Thinc's
built-in dataset loader. </s> remove             "Multi-threading": "multithreading",
 </s> add             "Multi-Threading": "multithreading",
    +h(3, "parallel-tag") Multi-processing with Joblib

    p
        |  This example shows how to use multiple cores to process text using
        |  spaCy and #[+a("https://pythonhosted.org/joblib/") Joblib]. We're
        |  exporting part-of-speech-tagged, true-cased, (very roughly)
        |  sentence-separated text, with each "sentence" on a newline, and
        |  spaces between tokens. Data is loaded from the IMDB movie reviews
        |  dataset and will be loaded automatically via Thinc's built-in dataset
        |  loader.

    +github("spacy", "examples/parallel_tag.py")

          |  #[code Span].
  
      +github("spacy", "examples/pipeline/custom_attr_methods.py")
  
    +h(3, "parallel-tag") Multi-processing with Joblib

    p
        |  This example shows how to use multiple cores to process text using
        |  spaCy and #[+a("https://pythonhosted.org/joblib/") Joblib]. We're
        |  exporting part-of-speech-tagged, true-cased, (very roughly)
        |  sentence-separated text, with each "sentence" on a newline, and
        |  spaces between tokens. Data is loaded from the IMDB movie reviews
        |  dataset and will be loaded automatically via Thinc's built-in dataset
        |  loader.

    +github("spacy", "examples/parallel_tag.py")

  +section("training")
      +h(3, "training-ner") Training spaCy's Named Entity Recognizer
  
      p
          |  This example shows how to update spaCy's entity recognizer
          |  with your own examples, starting off with an existing, pre-trained
keep keep keep add keep keep keep keep keep keep
 Update multi-processing example and add to docs 
website/usage/examples.jade