cannot load customized tokenizer with modified vocabulary
I have customized a tokenizer saved as tokenization_new.py and modified the vocab.txt from s3 server. I tried
`from transformers import NewBertTokenizer`
`tokenizer = NewBertTokenizer.from_pretrained('bert-base-uncased', do_lower_case=True)`
where I modified `PRETRAINED_VOCAB_FILES_MAP = {"vocab_file":{"bert-base-uncased": /vocab/vocab.txt},}`
where `/vocab/` is a directory parallel to tokenization_new.py that contains my customized vocabulary. However, I got an error raised as 
`Model name 'bert-base-uncased' was not found in tokenizers model name list (bert-base-uncased). We assumed 'bert-base-uncased' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.`
What should I do to use my own customized tokenizer? 
Thanks for the help!
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