model = joblib.load('TabPFN.pkl')
result = model.predict(feature_values)[0]
Report an error
result = model.predict(feature_values)
File "D:\apps\anaconda\envs\pytorch39\lib\site-packages\tabpfn_client\estimator.py", line 371, in predict
return InferenceClient.predict(
File "D:\apps\anaconda\envs\pytorch39\lib\site-packages\tabpfn_client\service_wrapper.py", line 251, in predict
return ServiceClient.predict(
File "D:\apps\anaconda\envs\pytorch39\lib\site-packages\tabpfn_client\client.py", line 292, in predict
) = cls.dataset_uid_cache_manager.get_dataset_uid(
File "D:\apps\anaconda\envs\pytorch39\lib\site-packages\tabpfn_client\client.py", line 86, in get_dataset_uid
dataset_hash = self._compute_hash(*args)
File "D:\apps\anaconda\envs\pytorch39\lib\site-packages\tabpfn_client\client.py", line 77, in _compute_hash
combined_bytes = b"".join(
File "D:\apps\anaconda\envs\pytorch39\lib\site-packages\tabpfn_client\client.py", line 78, in <genexpr>
item if isinstance(item, bytes) else str.encode(item) for item in args
TypeError: descriptor 'encode' for 'str' objects doesn't apply to a 'NoneType' object
