No proper tokenizer for 'switch-xxl-128'
#7
by VIArchitect - opened
Hello.
For example code execution,
It seems that there's no proper tokenizer for 'switch-xxl-128'
It shows an error below, and I used the example code in the model card with full-precision.
Traceback (most recent call last):
File "example.py", line 4, in <module>
tokenizer = AutoTokenizer.from_pretrained(
File "/root/hugging_face/hf/lib/python3.8/site-packages/transformers/models/auto/tokenization_auto.py", line 658, in from_pretrained
return tokenizer_class_fast.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
File "/root/hugging_face/hf/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 1761, in from_pretrained
raise EnvironmentError(
OSError: Can't load tokenizer for 'google/switch-xxl-128'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'google/switch-xxl-128' is the correct path to a directory containing all relevant files for a T5TokenizerFast tokenizer.
Thanks for pointing out the issue, the tokenizer was indeed missing, I have just uploaded it now!
Thanks, @ybelkada !
But it seems not to be working well...
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If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc 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
I just tried to download the tokenizer with the following:
from transformers import AutoTokenizer
tok = AutoTokenizer.from_pretrained("google/switch-xxl-128")
And seems to work fine
could you share the full error traceback?
Ok, this is the full error traceback
Traceback (most recent call last):
File "example.py", line 4, in <module>
tokenizer = AutoTokenizer.from_pretrained("google/switch-xxl-128", resume_download=True)
File "/root/hugging_face/hf/lib/python3.8/site-packages/transformers/models/auto/tokenization_auto.py", line 640, in from_pretrained
return tokenizer_class.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
File "/root/hugging_face/hf/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 1777, in from_pretrained
return cls._from_pretrained(
File "/root/hugging_face/hf/lib/python3.8/site-packages/transformers/tokenization_utils_base.py", line 1932, in _from_pretrained
tokenizer = cls(*init_inputs, **init_kwargs)
File "/root/hugging_face/hf/lib/python3.8/site-packages/transformers/models/t5/tokenization_t5_fast.py", line 134, in __init__
super().__init__(
File "/root/hugging_face/hf/lib/python3.8/site-packages/transformers/tokenization_utils_fast.py", line 114, in __init__
fast_tokenizer = convert_slow_tokenizer(slow_tokenizer)
File "/root/hugging_face/hf/lib/python3.8/site-packages/transformers/convert_slow_tokenizer.py", line 1162, in convert_slow_tokenizer
return converter_class(transformer_tokenizer).converted()
File "/root/hugging_face/hf/lib/python3.8/site-packages/transformers/convert_slow_tokenizer.py", line 438, in __init__
from .utils import sentencepiece_model_pb2 as model_pb2
File "/root/hugging_face/hf/lib/python3.8/site-packages/transformers/utils/sentencepiece_model_pb2.py", line 92, in <module>
_descriptor.EnumValueDescriptor(
File "/root/hugging_face/hf/lib/python3.8/site-packages/google/protobuf/descriptor.py", line 755, 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
Thanks!
Do you get the same error without resume_download?
Yes, I got the same error without resume_download:(
pip install --upgrade protobuf==3.20.0
This solves this problem.
VIArchitect changed discussion status to closed