input: from typing import Union
  
  def evaluate_model_accuracy(model: Union[SVC, int, float], X_train, y_train, X_test, y_test) -> float:
      """ Evaluates the accuracy of a machine-learning model using the provided training and test data.
      >>> evaluate_model_accuracy(SVC(kernel='poly', degree=2, gamma=0.05), X_train, y_train, X_test, y_test)
      0.95
      >>> evaluate_model_accuracy(SVC(kernel='linear', C=1.0), X_train, y_train, X_test, y_test)
      0.87
      """
      from sklearn.svm import SVC
      from sklearn.metrics import accuracy_score
      
      if not isinstance(model, SVC):
          raise ValueError("Model provided is not an instance of SVC.")
      
      model.fit(X_train, y_train)
      y_pred = model.predict(X_test)
      
      # Calculating the accuracy
      accuracy = accuracy_score(y_test, y_pred)
      return accuracy
output:     from sklearn.svm import SVC
      from sklearn.metrics import accuracy_score
      
      if not isinstance(model, SVC):
          raise ValueError("Model provided is not an instance of SVC.")
      
      model.fit(X_train, y_train)
      y_pred = model.predict(X_test)
      
      # Calculating the accuracy
      accuracy = accuracy_score(y_test, y_pred)
      return accuracy