AttributeError: ‘MPNetTokenizerFast’ object has no attribute ‘split_special_tokens’ after recent update in sentence-transformer==2.2.2
emr version 6.5
spark 3.2
python 3.8

Tried using another version but now it gives

sentence_transformer_model = pickle.loads(s3.Bucket(bucket_name).Object(object_path).get()[‘Body’].read())
Traceback (most recent call last):
File “”, line 1, in
File “/usr/local/lib64/python3.8/site-packages/torch/storage.py”, line 381, in _load_from_bytes
return torch.load(io.BytesIO(b))
File “/usr/local/lib64/python3.8/site-packages/torch/serialization.py”, line 1040, in load
return _legacy_load(opened_file, map_location, pickle_module, **pickle_load_args)
File “/usr/local/lib64/python3.8/site-packages/torch/serialization.py”, line 1272, in _legacy_load
result = unpickler.load()
File “/usr/local/lib64/python3.8/site-packages/torch/serialization.py”, line 1205, in persistent_load
obj = restore_location(obj, location)
File “/usr/local/lib64/python3.8/site-packages/torch/serialization.py”, line 390, in default_restore_location
result = fn(storage, location)
File “/usr/local/lib64/python3.8/site-packages/torch/serialization.py”, line 307, in mps_deserialize
return obj.mps()
File “/usr/local/lib64/python3.8/site-packages/torch/storage.py”, line 144, in mps
return torch.UntypedStorage(self.size(), device=”mps”).copy(self, False)
RuntimeError: torch.UntypedStorage(): Storage device not recognized: mps