code: def _load_network(self):
      
      self.embeddings = load_embeddings(self.lang, type='cw')
      self.model = load_pos_model(lang=self.lang, version=2)
  
      def predict_proba(input_):
        hidden = np.tanh(np.dot(input_, self.model["W1"]) + self.model["b1"])
        output =  np.dot(hidden, self.model["W2"]) + self.model["b2"]
        scores = np.exp(output)
        probs = scores/scores.sum()
        return probs
      return predict_proba
docs: Building the predictor out of the model.