runtime error

ocal/lib/python3.8/site-packages/tensorflow/core/framework/tensor_shape_pb2.py", line 36, in <module> _descriptor.FieldDescriptor( File "/home/user/.local/lib/python3.8/site-packages/google/protobuf/descriptor.py", line 561, in __new__ _message.Message._CheckCalledFromGeneratedFile() TypeError: Descriptors cannot not be created directly. If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0. If you cannot immediately regenerate your protos, some other possible workarounds are: 1. Downgrade the protobuf package to 3.20.x or lower. 2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower). More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates The above exception was the direct cause of the following exception: Traceback (most recent call last): File "app.py", line 2, in <module> from transformers import pipeline File "<frozen importlib._bootstrap>", line 1039, in _handle_fromlist File "/home/user/.local/lib/python3.8/site-packages/transformers/utils/import_utils.py", line 1089, in __getattr__ module = self._get_module(self._class_to_module[name]) File "/home/user/.local/lib/python3.8/site-packages/transformers/utils/import_utils.py", line 1101, in _get_module raise RuntimeError( RuntimeError: Failed to import transformers.pipelines because of the following error (look up to see its traceback): Descriptors cannot not be created directly. If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0. If you cannot immediately regenerate your protos, some other possible workarounds are: 1. Downgrade the protobuf package to 3.20.x or lower. 2. Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower). More information: https://developers.google.com/protocol-buffers/docs/news/2022-05-06#python-updates

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