code: def load(model_folder):
      with open(join(model_folder, "metadata.json")) as f:
          metadata = json.loads(f.read())
      if metadata["estimator"] == "SVC":
          estimator = TEXT_CLASSIFIER_ESTIMATOR.SVC
      if metadata["estimator"] == "FAST_TEXT":
          estimator = TEXT_CLASSIFIER_ESTIMATOR.FAST_TEXT
      if metadata["estimator"] == "PIPELINE":
          estimator = TEXT_CLASSIFIER_ESTIMATOR.PIPELINE
  
      # GH-304: remove fasttext
      # if estimator == TEXT_CLASSIFIER_ESTIMATOR.FAST_TEXT:
      #     model_file = join(model_folder, "model.bin")
      #     classifier = TextClassifier(estimator=TEXT_CLASSIFIER_ESTIMATOR.FAST_TEXT)
      #     classifier.ft = fastText.load_model(model_file)
      #     return classifier
  
      if estimator == TEXT_CLASSIFIER_ESTIMATOR.SVC:
          classifier = TextClassifier(
              estimator=TEXT_CLASSIFIER_ESTIMATOR.SVC
          )
          classifier.svc = joblib.load(
              join(model_folder, "estimator.joblib")
          )
          x_transformer = joblib.load(
              join(model_folder, "x_transformer.joblib")
          )
          classifier.x_transformer = x_transformer
          y_transformer = joblib.load(
              join(model_folder, "y_transformer.joblib")
          )
          classifier.y_transformer = y_transformer
          return classifier
  
      if estimator == TEXT_CLASSIFIER_ESTIMATOR.PIPELINE:
          classifier = TextClassifier(
              estimator=TEXT_CLASSIFIER_ESTIMATOR.PIPELINE
          )
          if "multilabel" in metadata:
              if metadata["multilabel"]:
                  classifier.multilabel = True
                  classifier.y_encoder = joblib.load(
                      join(model_folder, "y_encoder.joblib")
                  )
          classifier.pipeline = joblib.load(
              join(model_folder, "pipeline.joblib")
          )
  
          return classifier
  
file_path: underthesea/underthesea/models/text_classifier.py
imports: from enum import Enum
  from os.path import join
  import json
  import joblib
  from sklearn.preprocessing import MultiLabelBinarizer
  import warnings
  from underthesea.corpus.data import Sentence, Label
label_desc: Use image node_id 2 for calling the TextClassifier obj's underlying member method code with example usage: obj.load(model_folder) and returns: classifier, classifier