CODEWITHSUNDEEP
pythontransformer-modelhuggingface-tokenizers
user14251114
user14251114

Reputation:

OSError: Can't load tokenizer

I want to train an XLNET language model from scratch. First, I have trained a tokenizer as follows:

from tokenizers import ByteLevelBPETokenizer

# Initialize a tokenizer
tokenizer = ByteLevelBPETokenizer()
# Customize training
tokenizer.train(files='data.txt', min_frequency=2, special_tokens=[ #defualt vocab size
    "<s>",
    "<pad>",
    "</s>",
    "<unk>",
    "<mask>",
])
tokenizer.save_model("tokenizer model")

Finally, I will have two files in the given directory:

merges.txt
vocab.json

I have defined the following config for the model:

from transformers import XLNetConfig, XLNetModel
config = XLNetConfig()

Now, I want to recreate my tokenizer in transformers:

from transformers import XLNetTokenizerFast

tokenizer = XLNetTokenizerFast.from_pretrained("tokenizer model")

However, the following error appears:

File "dfgd.py", line 8, in <module>
    tokenizer = XLNetTokenizerFast.from_pretrained("tokenizer model")
  File "C:\Users\DSP\AppData\Roaming\Python\Python37\site-packages\transformers\tokenization_utils_base.py", line 1777, in from_pretrained
    raise EnvironmentError(msg)
OSError: Can't load tokenizer for 'tokenizer model'. Make sure that:

- 'tokenizer model' is a correct model identifier listed on 'https://huggingface.co/models'

- or 'tokenizer model' is the correct path to a directory containing relevant tokenizer files

What should I do?

Upvotes: 4

Views: 11942

Answers (1)

user14251114
user14251114

Reputation:

Instead of

tokenizer = XLNetTokenizerFast.from_pretrained("tokenizer model")

you should write:

from tokenizers.implementations import ByteLevelBPETokenizer
tokenizer = ByteLevelBPETokenizer(
    "tokenizer model/vocab.json",
    "tokenizer model/merges.txt",
)

Upvotes: 3

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