diff --git a/src/solvers/jump.jl b/src/solvers/jump.jl
index b7bb2b2..9a84d02 100644
--- a/src/solvers/jump.jl
+++ b/src/solvers/jump.jl
@@ -17,6 +17,15 @@ Base.@kwdef mutable struct _JumpModelExtData
     cuts_separate::Union{Function,Nothing} = nothing
 end
 
+function JuMP.copy_extension_data(
+    ::_JumpModelExtData,
+    new_model::AbstractModel,
+    ::AbstractModel,
+)
+    # Do not transfer any extension data to the new model
+    new_model.ext[:miplearn] = _JumpModelExtData()
+end
+
 # -----------------------------------------------------------------------------
 
 function _add_constrs(
diff --git a/test/src/components/test_cuts.jl b/test/src/components/test_cuts.jl
index 1562648..f466732 100644
--- a/test/src/components/test_cuts.jl
+++ b/test/src/components/test_cuts.jl
@@ -28,15 +28,13 @@ end
 
 function test_cuts()
     data_filenames = ["$BASEDIR/../fixtures/stab-n50-0000$i.pkl.gz" for i in 0:0]
-    clf = pyimport("sklearn.neighbors").KNeighborsClassifier(n_neighbors=1)
+    clf = pyimport("sklearn.dummy").DummyClassifier()
     extractor = H5FieldsExtractor(
         instance_fields=["static_var_obj_coeffs"],
     )
     comp = MemorizingCutsComponent(clf=clf, extractor=extractor)
     solver = LearningSolver(components=[comp])
     solver.fit(data_filenames)
-    @show comp.n_features_
-    @show comp.n_targets_
     stats = solver.optimize(
         data_filenames[1],
         data -> build_stab_model_jump(data, optimizer=SCIP.Optimizer),
diff --git a/test/src/problems/test_stab.jl b/test/src/problems/test_stab.jl
index 60f27b3..7a11a56 100644
--- a/test/src/problems/test_stab.jl
+++ b/test/src/problems/test_stab.jl
@@ -6,11 +6,6 @@ using PyCall
 using SCIP
 
 function test_problems_stab()
-    test_problems_stab_1()
-    test_problems_stab_2()
-end
-
-function test_problems_stab_1()
     nx = pyimport("networkx")
     data = MaxWeightStableSetData(
         graph=nx.gnp_random_graph(25, 0.5, seed=42),