class_docstr: Sentence Splitter using Spacy.
  
  Implementation of :class:`SentenceSplitter`, using models from Spacy.
  
  Args:
      model: Spacy V2 model or the name of the model to load.
      tokenizer: Custom tokenizer to use (default :class:`SpacyTokenizer`)
class_docstr_tok: ["Sentence","Splitter","using","Spacy",".","Implementation","of",":","class",":","`","SentenceSplitter","`",",","using","models","from","Spacy",".","Args",":","model",":","Spacy","V2","model","or","the","name","of","the","model","to","load",".","tokenizer",":","Custom","tokenizer","to","use","(","default",":","class",":","`","SpacyTokenizer","`",")"]
code: def split(self, text: str) -> List[Sentence]:
      document = self.model(text)
  
      sentences = [
          Sentence(
              text=str(spacy_sent),
              use_tokenizer=self._tokenizer,
              start_position=spacy_sent.start_char,
          )
          for spacy_sent in document.sents
          if len(str(spacy_sent)) > 0
      ]
  
      return sentences
  
imports: from abc import ABC, abstractmethod
  from typing import Any, List, Optional, Union
  from segtok.segmenter import split_multi
  from flair.data import Sentence
  from flair.tokenization import SciSpacyTokenizer, SegtokTokenizer, SpacyTokenizer, Tokenizer
label_desc: Use image node_id 2 for calling the SpacySentenceSplitter obj's underlying member method code with example usage: obj.split(text) and returns: sentences