diff --git a/GPy/examples/regression.py b/GPy/examples/regression.py
index 6c22b68e..f5d0d3b1 100644
--- a/GPy/examples/regression.py
+++ b/GPy/examples/regression.py
@@ -194,7 +194,7 @@ def multiple_optima(gene_number=937,resolution=80, model_restarts=10, seed=10000
     # Remove the mean (no bias kernel to ensure signal/noise is in RBF/white)
     data['Y'] = data['Y'] - np.mean(data['Y'])
 
-    lls = GPy.examples.regression.contour_data(data, length_scales, log_SNRs, GPy.kern.rbf)
+    lls = GPy.examples.regression._contour_data(data, length_scales, log_SNRs, GPy.kern.rbf)
     pb.contour(length_scales, log_SNRs, np.exp(lls), 20)
     ax = pb.gca()
     pb.xlabel('length scale')
@@ -229,7 +229,7 @@ def multiple_optima(gene_number=937,resolution=80, model_restarts=10, seed=10000
     ax.set_ylim(ylim)
     return (models, lls)
 
-def contour_data(data, length_scales, log_SNRs, signal_kernel_call=GPy.kern.rbf):
+def _contour_data(data, length_scales, log_SNRs, signal_kernel_call=GPy.kern.rbf):
     """Evaluate the GP objective function for a given data set for a range of signal to noise ratios and a range of lengthscales.
 
     :data_set: A data set from the utils.datasets director.
diff --git a/GPy/examples/tutorials.py b/GPy/examples/tutorials.py
index 9d892b8e..a199aba9 100644
--- a/GPy/examples/tutorials.py
+++ b/GPy/examples/tutorials.py
@@ -6,14 +6,14 @@
 Code of Tutorials
 """
 
+import pylab as pb
+pb.ion()
+import numpy as np
+import GPy
+
 def tuto_GP_regression():
     """The detailed explanations of the commands used in this file can be found in the tutorial section"""
 
-    import pylab as pb
-    pb.ion()
-    import numpy as np
-    import GPy
-
     X = np.random.uniform(-3.,3.,(20,1))
     Y = np.sin(X) + np.random.randn(20,1)*0.05
 
@@ -39,11 +39,6 @@ def tuto_GP_regression():
     #  2-dimensional example  #
     ###########################
 
-    import pylab as pb
-    pb.ion()
-    import numpy as np
-    import GPy
-
     # sample inputs and outputs
     X = np.random.uniform(-3.,3.,(50,2))
     Y = np.sin(X[:,0:1]) * np.sin(X[:,1:2])+np.random.randn(50,1)*0.05
@@ -67,9 +62,6 @@ def tuto_GP_regression():
 
 def tuto_kernel_overview():
     """The detailed explanations of the commands used in this file can be found in the tutorial section"""
-    import pylab as pb
-    import numpy as np
-    import GPy
     pb.ion()
 
     ker1 = GPy.kern.rbf(1)  # Equivalent to ker1 = GPy.kern.rbf(D=1, variance=1., lengthscale=1.)
diff --git a/GPy/testing/examples_tests.py b/GPy/testing/examples_tests.py
index 0e41a541..967d7a6a 100644
--- a/GPy/testing/examples_tests.py
+++ b/GPy/testing/examples_tests.py
@@ -4,23 +4,63 @@
 import unittest
 import numpy as np
 import GPy
+import inspect
+import pkgutil
+import os
+
 
 class ExamplesTests(unittest.TestCase):
-    def test_check_model_returned(self):
-        pass
+    def _checkgrad(self, model):
+        self.assertTrue(model.checkgrad())
 
-    def test_model_checkgrads(self):
-        pass
+    def _model_instance(self, model):
+        self.assertTrue(isinstance(model, GPy.models))
 
-    def test_all_examples(self):
-        examples_module = __import__("GPy").examples
-        #Load models
+"""
+def model_instance_generator(model):
+    def check_model_returned(self):
+        self._model_instance(model)
+    return check_model_returned
 
-        #Loop through models
-        #for model in models:
-            #self.assertTrue(m.checkgrad())
+def checkgrads_generator(model):
+    def model_checkgrads(self):
+        self._checkgrad(model)
+    return model_checkgrads
+"""
+def model_checkgrads(model):
+    assert model.checkgrad() is True
 
+def model_instance(model):
+    assert model.checkgrad() is True
+
+def test_models():
+    examples_path = os.path.dirname(GPy.examples.__file__)
+    #Load modules
+    for loader, module_name, is_pkg in pkgutil.iter_modules([examples_path]):
+        #Load examples
+        module_examples = loader.find_module(module_name).load_module(module_name)
+        functions = [ func for func in [inspect.getmembers(module_examples, predicate=inspect.isfunction)[0]] if func[0].startswith('_') is False ]
+        for example in functions:
+            print "Testing example: ", example[0]
+            #Generate model
+            model = example[1]()
+            print model
+
+            #Create tests for instance check
+            """
+            test = model_instance_generator(model)
+            test.__name__ = 'test_instance_%s' % example[0]
+            setattr(ExamplesTests, test.__name__, test)
+
+            #Create tests for checkgrads check
+            test = checkgrads_generator(model)
+            test.__name__ = 'test_checkgrads_%s' % example[0]
+            setattr(ExamplesTests, test.__name__, test)
+            """
+            model_checkgrads.description = 'test_checkgrads_%s' % example[0]
+            yield model_checkgrads, model
+            model_instance.description = 'test_checkgrads_%s' % example[0]
+            yield model_instance, model
 
 if __name__ == "__main__":
     print "Running unit tests, please be (very) patient..."
-    unittest.main()