text: import en_core_sci_lg
  import spacy
  from spacy.lang.en import English
  
  # Load English tokenizer, tagger, parser, NER and word vectors
  def word_tokenizer(input_text):
      nlp = English()
      my_doc = nlp(input_text)
  
      # Create list of word tokens
      token_list = []
      for token in my_doc:
          token_list.append(token.text)
      return {"word_tokens":token_list}
  
  def sentence_tokenizer(input_text):
      input_text = input_text.replace('\n','')
      nlp = spacy.load('en_core_web_sm',disable=['lemmatizer'])
      doc = nlp(input_text)
      sents_list = []
      for sent in doc.sents:
          sents_list.append(sent.text)
      return {"sentence_tokens":sents_list}