The data generation example is broken

[LeoGrin]

Running examples/unsupervised/generate_data.py gives:

Traceback (most recent call last):
  File "/Users/leo/VSCProjects/tabpfn-extensions/examples/unsupervised/generate_data.py", line 43, in <module>
    results = exp_synthetic.run(
  File "/Users/leo/VSCProjects/tabpfn-extensions/src/tabpfn_extensions/unsupervised/experiments.py", line 132, in run
    self.synthetic_X = tabpfn.generate_synthetic_data(n_samples=n_samples, t=temp)
  File "/Users/leo/VSCProjects/tabpfn-extensions/src/tabpfn_extensions/unsupervised/unsupervised.py", line 410, in generate_synthetic_data
    return self.impute_(
  File "/Users/leo/VSCProjects/tabpfn-extensions/src/tabpfn_extensions/unsupervised/unsupervised.py", line 158, in impute_
    _, pred = self.impute_single_permutation_(
  File "/Users/leo/VSCProjects/tabpfn-extensions/src/tabpfn_extensions/unsupervised/unsupervised.py", line 214, in impute_single_permutation_
    model, X_predict, _ = self.density_(
  File "/Users/leo/VSCProjects/tabpfn-extensions/src/tabpfn_extensions/unsupervised/unsupervised.py", line 278, in density_
    model.fit(X_fit.numpy(), y_fit.numpy())
  File "/Users/leo/mambaforge/envs/tabpfn_extensions_env/lib/python3.10/site-packages/tabpfn/classifier.py", line 414, in fit
    X, y, feature_names_in, n_features_in = validate_Xy_fit(
  File "/Users/leo/mambaforge/envs/tabpfn_extensions_env/lib/python3.10/site-packages/tabpfn/utils.py", line 521, in validate_Xy_fit
    check_classification_targets(y)
  File "/Users/leo/mambaforge/envs/tabpfn_extensions_env/lib/python3.10/site-packages/sklearn/utils/multiclass.py", line 222, in check_classification_targets
    raise ValueError(
ValueError: Unknown label type: continuous. Maybe you are trying to fit a classifier, which expects discrete classes on a regression target with continuous values.