diff --git a/onnxruntime_extensions/pnp/_nlp.py b/onnxruntime_extensions/pnp/_nlp.py
index f8f89fa0..f8447910 100644
--- a/onnxruntime_extensions/pnp/_nlp.py
+++ b/onnxruntime_extensions/pnp/_nlp.py
@@ -16,16 +16,21 @@ def make_custom_op(ctx, op_type, input_names, output_names, container, operator_
         outputs=((_dt.INT64, []), (_dt.INT64, []), (_dt.INT64, [])))
 def bert_tokenize(ctx, input_names, output_names, container, operator_name=None, **kwargs):
     if 'hf_tok' in kwargs:
-        # TODO: need bert-tokenizer support JSON format
         hf_bert_tokenizer = kwargs['hf_tok']
-        attrs = {'vocab_file': json.dumps(hf_bert_tokenizer.vocab, separators=(',', ':'))}
+        attrs = {'vocab_file': hf_bert_tokenizer.vocab}
     elif 'vocab_file' in kwargs:
-        attrs = dict(vocab_file=kwargs['vocab_file'])
+        vocab = None
+        vocab_file = kwargs['vocab_file']
+        with open(vocab_file, "r", encoding='utf-8') as vf:
+            lines = vf.readlines()
+            vocab = '\n'.join(lines)
+        if vocab is None:
+            raise RuntimeError("Cannot load vocabulary file {}!".format(vocab_file))
+        attrs = dict(vocab_file=vocab)
     else:
         raise RuntimeError("Need hf_tok/vocab_file parameter to build the tokenizer")
     if 'strip_accents' in kwargs:
-        strip_accents = kwargs['strip_accents']
-        attrs['strip_accents'] = strip_accents
+        attrs['strip_accents'] = kwargs['strip_accents']
 
     return make_custom_op(ctx, 'BertTokenizer', input_names,
                           output_names, container, operator_name=operator_name, **attrs)
@@ -67,18 +72,12 @@ class PreHuggingFaceBert(ProcessingTracedModule):
     def __init__(self, hf_tok=None, vocab_file=None, do_lower_case=0, strip_accents=1):
         super(PreHuggingFaceBert, self).__init__()
         if hf_tok is None:
-            _vocab = None
-            with open(vocab_file, "r", encoding='utf-8') as vf:
-                lines = vf.readlines()
-                _vocab = '\n'.join(lines)
-            if _vocab is None:
-                raise RuntimeError("Cannot load vocabulary file {}!".format(vocab_file))
             self.onnx_bert_tokenize = create_op_function('BertTokenizer', bert_tokenize,
-                                                         vocab_file=_vocab,
+                                                         vocab_file=vocab_file,
                                                          do_lower_case=do_lower_case,
                                                          strip_accents=strip_accents)
         else:
-            self.onnx_bert_tokenize = create_op_function('BertTokenizer', bert_tokenize, hf_tok=self.hf_tok)
+            self.onnx_bert_tokenize = create_op_function('BertTokenizer', bert_tokenize, hf_tok=hf_tok)
 
     def forward(self, text):
         return self.onnx_bert_tokenize(text)
@@ -96,7 +95,7 @@ class PreHuggingFaceGPT2(ProcessingTracedModule):
                                                          merges=_get_file_content(merges_file),
                                                          padding_length=padding_length)
         else:
-            self.onnx_gpt2_tokenize = create_op_function('GPT2Tokenizer', gpt2_tokenize, hf_tok=self.hf_tok)
+            self.onnx_gpt2_tokenize = create_op_function('GPT2Tokenizer', gpt2_tokenize, hf_tok=hf_tok)
 
     def forward(self, text):
         return self.onnx_gpt2_tokenize(text)