class_docstr: Classifier based on cosine similarity between vectorized sentences
  
  Parameters:
      save_path: path to save the model
      load_path: path to load the model
class_docstr_tok: ["Classifier","based","on","cosine","similarity","between","vectorized","sentences","Parameters",":","save_path",":","path","to","save","the","model","load_path",":","path","to","load","the","model"]
docstr: Save classifier parameters
docstr_tok: ["Save","classifier","parameters"]
code: def save(self) -> None:
      """Save classifier parameters"""
      logger.info("Saving faq_model to {}".format(self.save_path))
      save_pickle((self.x_train_features, self.y_train), self.save_path)
  
file_path: DeepPavlov/deeppavlov/models/classifiers/cos_sim_classifier.py
imports: from logging import getLogger
  from typing import List, Tuple, Union
  import numpy
  from scipy.sparse import vstack, csr_matrix
  from scipy.sparse.linalg import norm
  from deeppavlov.core.common.file import load_pickle
  from deeppavlov.core.common.file import save_pickle
  from deeppavlov.core.common.registry import register
  from deeppavlov.core.models.estimator import Estimator
  from deeppavlov.core.models.serializable import Serializable
label_desc: Use image node_id 4 for calling the CosineSimilarityClassifier obj's underlying member method code with example usage: obj.save() without return types