diff --git a/cmake/ext_ortlib.cmake b/cmake/ext_ortlib.cmake
index 49dd05c8a..53fe00932 100644
--- a/cmake/ext_ortlib.cmake
+++ b/cmake/ext_ortlib.cmake
@@ -34,7 +34,7 @@ else()
   if (OCOS_ONNXRUNTIME_VERSION)
     set(ONNXRUNTIME_VER ${OCOS_ONNXRUNTIME_VERSION})
   else()
-    set(ONNXRUNTIME_VER "1.17.1")
+    set(ONNXRUNTIME_VER "1.19.2")     # need to check if android package of this version is available too.
   endif()
 
   if (ANDROID)
diff --git a/include/ort_c_to_cpp.h b/include/ort_c_to_cpp.h
index a10618ae8..5d26a5831 100644
--- a/include/ort_c_to_cpp.h
+++ b/include/ort_c_to_cpp.h
@@ -395,7 +395,7 @@ inline bool IsScalarOr1ElementVector(size_t num_dimensions, int64_t shape_size)
   return false;
 }
 
-#define ORTX_RETURN_IF_ERROR(expr) \
+#define ORTW_RETURN_IF_ERROR(expr) \
   do {                             \
     auto _status = (expr);         \
     if (_status != nullptr) {      \
diff --git a/include/ortx_tokenizer.h b/include/ortx_tokenizer.h
index 9558d1e77..e51a5bd5f 100644
--- a/include/ortx_tokenizer.h
+++ b/include/ortx_tokenizer.h
@@ -29,8 +29,8 @@ struct OrtxTokenizerBlob {
 #ifdef __cplusplus
   OrtxTokenizerBlob(const std::string_view& config_json_blob,
                     const std::string_view& vocab_json_blob,
-                    const std::string_view& token_module_blob,
-                    const std::string_view& raw_model_blob)
+                    const std::string_view& token_module_blob = {},
+                    const std::string_view& raw_model_blob = {})
       : config_json_blob(config_json_blob.data()), vocab_json_blob(vocab_json_blob.data()),
         token_module_blob(token_module_blob.data()), raw_model_blob(raw_model_blob.data()),
         config_blob_len(config_json_blob.size()),
diff --git a/include/ortx_utils.h b/include/ortx_utils.h
index 59f101347..240874c30 100644
--- a/include/ortx_utils.h
+++ b/include/ortx_utils.h
@@ -37,6 +37,14 @@ typedef OrtxObject OrtxTensorResult;
 // C, instead of C++ doesn't cast automatically,
 // so we need to use a macro to cast the object to the correct type
 #define ORTX_DISPOSE(obj) OrtxDispose((OrtxObject**)&obj)
+#define ORTX_RETURN_IF_ERROR(expr) \
+  do {                             \
+    auto _status = (expr);         \
+    if (!_status.IsOk()) {      \
+      return _status;              \
+    }                              \
+  } while (0)
+
 
 typedef uint32_t extTokenId_t;
 
diff --git a/onnxruntime_extensions/_cuops.py b/onnxruntime_extensions/_cuops.py
index 8d0cf3bd8..6be03a9b2 100644
--- a/onnxruntime_extensions/_cuops.py
+++ b/onnxruntime_extensions/_cuops.py
@@ -491,6 +491,16 @@ def get_outputs(cls):
         ]
 
 
+class HfJsonTokenizer(CustomOp):
+    @classmethod
+    def get_inputs(cls):
+        return [cls.io_def('str', onnx_proto.TensorProto.STRING, ['N'])]
+
+    @classmethod
+    def get_outputs(cls):
+        return [cls.io_def("ids", onnx.TensorProto.INT64, ['N', None])]
+
+
 # TODO: have a C++ impl.
 def _argsort_op(x, dim):
     d = numpy.argsort(x, dim)
@@ -544,4 +554,4 @@ def build_graph(cls, op_class, *args, **kwargs):
 
     @staticmethod
     def get_op_class(op_type):
-        return globals()[op_type]
+        return globals()[op_type]
\ No newline at end of file
diff --git a/onnxruntime_extensions/cvt.py b/onnxruntime_extensions/cvt.py
index 820964155..307bffabb 100644
--- a/onnxruntime_extensions/cvt.py
+++ b/onnxruntime_extensions/cvt.py
@@ -12,6 +12,24 @@
 from ._hf_cvt import HFTokenizerConverter, HFTokenizerOnnxGraph  # noqa
 from ._ortapi2 import make_onnx_model, SingleOpGraph
 
+import os
+import numpy as np
+import tempfile
+import shutil
+
+# edit environment variables to avoid protobuf version mismatch
+os.environ["PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION"] = "python"
+
+from transformers.convert_slow_tokenizer import SpmConverter  # noqa: E402
+from transformers import AutoTokenizer  # noqa: E402
+from tokenizers import decoders, normalizers, pre_tokenizers, Regex  # noqa: E402
+
+
+OrtxTokenizer = None
+try:
+    from onnxruntime_extensions.pp_api import Tokenizer as OrtxTokenizer
+except ImportError:
+    pass
 
 _is_torch_available = False
 try:
@@ -24,11 +42,150 @@
 
 _PRE_POST_PAIR = {'TrieTokenizer': "TrieDetokenizer"}
 
+def _get_prepend_scheme(add_prefix_space: bool, original_tokenizer) -> str:
+    if add_prefix_space:
+        prepend_scheme = "always"
+        if not getattr(original_tokenizer, "legacy", True):
+            prepend_scheme = "first"
+    else:
+        prepend_scheme = "never"
+    return prepend_scheme
+
+
+class Baichuan2Converter(SpmConverter):
+    handle_byte_fallback = True
+
+    def __init__(self, original_tokenizer):
+        super().__init__(original_tokenizer)
+        original_tokenizer.add_prefix_space = False
+
+    def vocab(self, proto):
+        vocab = [
+            (self.original_tokenizer.convert_ids_to_tokens(0), 0.0),
+            (self.original_tokenizer.convert_ids_to_tokens(1), 0.0),
+            (self.original_tokenizer.convert_ids_to_tokens(2), 0.0),
+        ]
+        vocab += [(piece.piece, piece.score) for piece in proto.pieces[3:]]
+        return vocab
+
+    def unk_id(self, proto):
+        unk_id = 0
+        return unk_id
+
+    def decoder(self, replacement, add_prefix_space):
+        sequence = [
+            decoders.Replace("▁", " "),
+            decoders.ByteFallback(),
+            decoders.Fuse(),
+        ]
+        if add_prefix_space:
+            sequence += [decoders.Strip(content=" ", left=1)]
+        return decoders.Sequence(sequence)
+
+    def normalizer(self, proto):
+        if getattr(self.original_tokenizer, "legacy", True):
+            sequence = []
+            if getattr(self.original_tokenizer, "add_prefix_space", True):
+                sequence += [normalizers.Prepend(prepend="▁")]
+            sequence += [normalizers.Replace(pattern=" ", content="▁")]
+            return normalizers.Sequence(sequence)
+        return None  # non-legacy, no normalizer
+
+    def pre_tokenizer(self, replacement, add_prefix_space):
+        if not getattr(self.original_tokenizer, "legacy", True):  # non-legacy, we need a replace
+            prepend_scheme = _get_prepend_scheme(add_prefix_space, self.original_tokenizer)
+            return pre_tokenizers.Metaspace(replacement=replacement, prepend_scheme=prepend_scheme, split=False)
+        else:
+            return super().pre_tokenizer(replacement, add_prefix_space)
+
+
+class ChatGlmConverter(SpmConverter):
+    def normalizer(self, proto):
+        precompiled_charsmap = proto.normalizer_spec.precompiled_charsmap
+        _normalizers = [
+            normalizers.Strip(left=False, right=True),  # stripping is important
+            normalizers.Replace(Regex(" {2,}"), "▁"),
+        ]
+        return normalizers.Sequence([normalizers.Precompiled(precompiled_charsmap)] + _normalizers)
+
+    def pre_tokenizer(self, replacement, add_prefix_space):
+        prepend_scheme = "always"
+        if hasattr(self.original_tokenizer, "legacy") and not self.original_tokenizer.legacy:
+            prepend_scheme = "first"
+        return pre_tokenizers.Metaspace(
+            replacement=replacement, add_prefix_space=add_prefix_space, prepend_scheme=prepend_scheme
+        )
+
+
+JSON_TOKEN_CONVERTERS = {
+    "BaichuanTokenizer": Baichuan2Converter,
+    "ChatGLMTokenizer": ChatGlmConverter,
+}
+
+# Save tokenizer JSON files using HuggingFace AutoTokenizer
+def convert_tokenizer(model_path, output_dir):
+    tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
+    if output_dir is None:
+        if os.path.isdir(model_path):
+            output_dir = model_path
+        else:
+            # create a temporary directory
+            output_dir = tempfile.mkdtemp()
+            tokenizer.save_pretrained(output_dir)
+        json_path = os.path.join(output_dir, "tokenizer.json")
+
+    if type(tokenizer).__name__ in JSON_TOKEN_CONVERTERS:
+        GenericSpmConverter = JSON_TOKEN_CONVERTERS[type(tokenizer).__name__]
+
+    converted = GenericSpmConverter(tokenizer).converted()
+    converted.save(json_path)
+    print(f"**Tokenizer saved to {json_path}")
+    return output_dir
+
+# Validate tokenizer files downloaded from memory
+def validate_tokenizer(model_path, output_dir):
+    test_sentence = "I like walking my cute dog\n and\x17 then, 生活的真谛是   \t\t\t\t \n\n61"
+    if OrtxTokenizer is None:
+        print("onnxruntime_extensions package was built with C API enabled, skipping tokenization test")
+    ortx_tokenizer = OrtxTokenizer(output_dir)
+    tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True, use_fast=False)
+    expected_ids = tokenizer(test_sentence, return_tensors="np")["input_ids"]
+    ortx_ids = np.asarray(ortx_tokenizer.tokenize(test_sentence))
+    assert np.array_equal(expected_ids[0], ortx_ids), f"Tokenization mismatch: {expected_ids[0]} != {ortx_ids}"
+    print("Tokenization test passed")
+
+# Download tokenizer JSON files from memory
+def download_tokenizer(tokenizer_dir, output_dir):
+    try:
+        from transformers.utils import cached_file
+
+        resolved_full_file = cached_file(tokenizer_dir, "tokenizer.json")
+        resolved_config_file = cached_file(tokenizer_dir, "tokenizer_config.json")
+    except ImportError:
+        raise ValueError(f"Directory '{tokenizer_dir}' not found and transformers is not available")
+    if not os.path.exists(resolved_full_file):
+        raise FileNotFoundError(f"Downloaded HF file '{resolved_full_file}' cannot be found")
+    if os.path.dirname(resolved_full_file) != os.path.dirname(resolved_config_file):
+        raise FileNotFoundError(
+            f"Downloaded HF files '{resolved_full_file}' " f"and '{resolved_config_file}' are not in the same directory"
+        )
+
+    if output_dir is None or len(output_dir) == 0:
+        output_dir = os.path.dirname(resolved_full_file)
+        print(f"Using {output_dir} as output directory")
+        return output_dir
+    else:
+        # copy the files to the output directory
+        shutil.copy(resolved_full_file, output_dir)
+        shutil.copy(resolved_config_file, output_dir)
+        return output_dir
+
 
 def gen_processing_models(processor: Union[str, object],
                           pre_kwargs: dict = None,
                           post_kwargs: dict = None,
                           opset: int = None,
+                          schema_v2: bool = False,
                           **kwargs):
     """
     Generate the pre- and post-processing ONNX model, basing on the name or HF class.
@@ -47,6 +204,9 @@ def gen_processing_models(processor: Union[str, object],
         Keyword arguments for generating the post-processing model
     opset: int
         the target opset version of the model
+    schema_v2: bool
+        the flag for using embedded tokenizer files; this option leverages the blob-loading functionality
+        which loads HF tokenizers from memory rather than using the tokenizer files in HF JSON format.
     kwargs:
         The additional arguments for generating models
 
@@ -58,11 +218,42 @@ def gen_processing_models(processor: Union[str, object],
     if pre_kwargs is None and post_kwargs is None:
         raise ValueError(
             "Either pre_kwargs or post_kwargs should be provided. None means no processing graph output.")
-    if isinstance(processor, str):
+
+    # If true, we get the tokenizer JSON files by either downloading from cache or using HuggingFace AutoTokenizer
+    # to convert them, and then create an ONNX model with the JSON files as strings in the model attributes (attrs).
+    if schema_v2:
+        model_name = processor if isinstance(processor, str) else type(processor).__name__
+
+        converted_tokenizer = {"Baichuan2", "chatglm"}
+        need_convert = False
+        for token in converted_tokenizer:
+            if model_name.find(token) != -1:
+                need_convert = True
+                break
+
+        if need_convert:
+            model_dir = convert_tokenizer(model_name)
+            validate_tokenizer(model_name, None)
+        else:
+            model_dir = download_tokenizer(model_name, None)
+
+        # Load the content of tokenizer.json into a string
+        with open(f"{model_dir}/tokenizer.json", "r", encoding="utf-8") as f:
+            tokenizer_vocab = f.read()
+
+        # Load the content of tokenizer_config.json into a string
+        with open(f"{model_dir}/tokenizer_config.json", "r", encoding="utf-8") as f:
+            tokenizer_config = f.read()
+
+        # Create an ONNX model with these JSON file strings in attrs
         g_pre, g_post = (None, None)
-        if pre_kwargs:
-            g_pre = SingleOpGraph.build_graph(processor, **pre_kwargs)
-        if post_kwargs:
+        if pre_kwargs is not None:
+            # Add tokenizer_vocab and tokenizer_config to the kwargs
+            # so they are added to attrs in build_graph
+            pre_kwargs['tokenizer_vocab'] = tokenizer_vocab
+            pre_kwargs['tokenizer_config'] = tokenizer_config
+            g_pre = SingleOpGraph.build_graph("HfJsonTokenizer", **pre_kwargs)
+        if post_kwargs is not None:
             if pre_kwargs is None:
                 cls_name = processor
             else:
@@ -70,27 +261,46 @@ def gen_processing_models(processor: Union[str, object],
                     raise RuntimeError(
                         f"Cannot locate the post processing operator name from {processor}")
                 cls_name = _PRE_POST_PAIR[processor]
+            # Add tokenizer_vocab and tokenizer_config to the kwargs
+            # so they are added to attrs in build_graph
+            post_kwargs['tokenizer_vocab'] = tokenizer_vocab
+            post_kwargs['tokenizer_config'] = tokenizer_config
             g_post = SingleOpGraph.build_graph(cls_name, **post_kwargs)
         return make_onnx_model(g_pre) if g_pre else None, make_onnx_model(g_post) if g_post else None
-
-    cls_name = type(processor).__name__
-    if cls_name == "WhisperProcessor":
-        if WhisperDataProcGraph is None:
-            raise ValueError(
-                "The Whisper processor needs torch.onnx support, please install pytorch 2.0 and above")
-        _converter = WhisperDataProcGraph(processor, opset=opset, **kwargs)
-        pre_m = _converter.pre_processing(
-            **pre_kwargs) if pre_kwargs is not None else None
-        post_m = _converter.post_processing(
-            **post_kwargs) if post_kwargs is not None else None
-        return pre_m, post_m
-    elif HFTokenizerOnnxGraph.is_supported(processor):
-        _converter = HFTokenizerOnnxGraph(processor)
-        pre_g = _converter.pre_processing(
-            **pre_kwargs) if pre_kwargs is not None else None
-        post_g = _converter.post_processing(
-            **post_kwargs) if post_kwargs is not None else None
-        return make_onnx_model(pre_g) if pre_g else None, \
-            make_onnx_model(post_g) if post_g else None
     else:
-        raise ValueError(f"Unsupported processor/tokenizer: {cls_name}")
+        if isinstance(processor, str):
+            g_pre, g_post = (None, None)
+            if pre_kwargs:
+                g_pre = SingleOpGraph.build_graph(processor, **pre_kwargs)
+            if post_kwargs:
+                if pre_kwargs is None:
+                    cls_name = processor
+                else:
+                    if processor not in _PRE_POST_PAIR:
+                        raise RuntimeError(
+                            f"Cannot locate the post processing operator name from {processor}")
+                    cls_name = _PRE_POST_PAIR[processor]
+                g_post = SingleOpGraph.build_graph(cls_name, **post_kwargs)
+            return make_onnx_model(g_pre) if g_pre else None, make_onnx_model(g_post) if g_post else None
+
+        cls_name = type(processor).__name__
+        if cls_name == "WhisperProcessor":
+            if WhisperDataProcGraph is None:
+                raise ValueError(
+                    "The Whisper processor needs torch.onnx support, please install pytorch 2.0 and above")
+            _converter = WhisperDataProcGraph(processor, opset=opset, **kwargs)
+            pre_m = _converter.pre_processing(
+                **pre_kwargs) if pre_kwargs is not None else None
+            post_m = _converter.post_processing(
+                **post_kwargs) if post_kwargs is not None else None
+            return pre_m, post_m
+        elif HFTokenizerOnnxGraph.is_supported(processor):
+            _converter = HFTokenizerOnnxGraph(processor)
+            pre_g = _converter.pre_processing(
+                **pre_kwargs) if pre_kwargs is not None else None
+            post_g = _converter.post_processing(
+                **post_kwargs) if post_kwargs is not None else None
+            return make_onnx_model(pre_g) if pre_g else None, \
+                make_onnx_model(post_g) if post_g else None
+        else:
+            raise ValueError(f"Unsupported processor/tokenizer: {cls_name}")
\ No newline at end of file
diff --git a/operators/tokenizer/bpe_decoder.hpp b/operators/tokenizer/bpe_decoder.hpp
index fb0a8d1e5..1cbb5a06e 100644
--- a/operators/tokenizer/bpe_decoder.hpp
+++ b/operators/tokenizer/bpe_decoder.hpp
@@ -49,26 +49,26 @@ struct KernelBpeDecoder {
     }
 
     std::string added_tokens;
-    ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "added_tokens", added_tokens));
+    ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "added_tokens", added_tokens));
     if (!added_tokens.empty()) {
       auto um = ParseId2String(added_tokens);
       added_tokens_ = std::map<int64_t, std::string>(um.begin(), um.end());
     }
 
     std::string all_special_ids;
-    ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "all_special_ids", all_special_ids));
+    ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "all_special_ids", all_special_ids));
     if (!all_special_ids.empty()) {
       auto um = ParseId2String(all_special_ids);
       std::transform(um.begin(), um.end(), std::inserter(all_special_ids_, all_special_ids_.end()),
                      [](const auto& p) { return p.first; });
     }
 
-    ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "en_normalization", en_normalization_));
-    ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "skip_special_tokens", skip_special_tokens_));
-    ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "whitespace_token", whitespace_token_));
-    ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "bos_token", bos_token_));
-    ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "eos_token", eos_token_));
-    ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "unk_token", unk_token_));
+    ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "en_normalization", en_normalization_));
+    ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "skip_special_tokens", skip_special_tokens_));
+    ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "whitespace_token", whitespace_token_));
+    ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "bos_token", bos_token_));
+    ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "eos_token", eos_token_));
+    ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "unk_token", unk_token_));
 
     return status;
   }
diff --git a/operators/tokenizer/bpe_kernels.cc b/operators/tokenizer/bpe_kernels.cc
index d5f27b81f..4ca160c9f 100644
--- a/operators/tokenizer/bpe_kernels.cc
+++ b/operators/tokenizer/bpe_kernels.cc
@@ -124,24 +124,24 @@ KernelBpeTokenizer::KernelBpeTokenizer(const BpeModelConf& conf)
 OrtStatusPtr KernelBpeTokenizer::OnModelAttach(const OrtApi& api, const OrtKernelInfo& info) {
   // note: if the attribute doesn't exist in op node, GetOpAttribute doesn't return a failed status;
   std::string vocab;
-  ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "vocab", vocab));
+  ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "vocab", vocab));
   if (vocab.empty()) {
     return OrtW::CreateStatus("vocabulary shouldn't be empty.", ORT_INVALID_ARGUMENT);
   }
 
   std::string merges;
-  ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "merges", merges));
+  ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "merges", merges));
   if (merges.empty()) {
     return OrtW::CreateStatus("merges shouldn't be empty.", ORT_INVALID_ARGUMENT);
   }
 
-  ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "padding_length", padding_length_));
+  ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "padding_length", padding_length_));
   if (padding_length_ != -1 && padding_length_ <= 0) {
     return OrtW::CreateStatus("padding_length should be more than 0 or equal -1", ORT_INVALID_ARGUMENT);
   }
 
   std::string model_name;
-  ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "model_name", model_name));
+  ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "model_name", model_name));
   if (!model_name.empty()) {
     model_name_ = model_name;
   }
@@ -159,7 +159,7 @@ OrtStatusPtr KernelBpeTokenizer::OnModelAttach(const OrtApi& api, const OrtKerne
   }
 
   std::string added_token;
-  ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "added_token", added_token));
+  ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "added_token", added_token));
   status = bbpe_tokenizer_->LoadAddedTokens(added_token.c_str());
   if (!status.IsOk()) {
     return (OrtStatusPtr)status;
diff --git a/operators/tokenizer/sentencepiece_decoder.hpp b/operators/tokenizer/sentencepiece_decoder.hpp
index b7e64873d..3f592ae93 100644
--- a/operators/tokenizer/sentencepiece_decoder.hpp
+++ b/operators/tokenizer/sentencepiece_decoder.hpp
@@ -12,7 +12,7 @@
 struct KernelSentencepieceDecoder {
   OrtStatusPtr OnModelAttach(const OrtApi& api, const OrtKernelInfo& info) {
     std::string model_blob;
-    ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "model", model_blob));
+    ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "model", model_blob));
 
     sentencepiece::ModelProto model_proto;
     model_proto.ParseFromArray(model_blob.data(), static_cast<int>(model_blob.size()));
diff --git a/operators/tokenizer/sentencepiece_tokenizer.cc b/operators/tokenizer/sentencepiece_tokenizer.cc
index e44217287..867a018b6 100644
--- a/operators/tokenizer/sentencepiece_tokenizer.cc
+++ b/operators/tokenizer/sentencepiece_tokenizer.cc
@@ -11,7 +11,7 @@
 
 OrtStatusPtr KernelSentencepieceTokenizer::OnModelAttach(const OrtApi& api, const OrtKernelInfo& info) {
   std::string model_as_string;
-  ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "model", model_as_string));
+  ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "model", model_as_string));
 
   sentencepiece::ModelProto model_proto;
   std::vector<uint8_t> model_as_bytes;
diff --git a/operators/tokenizer/tokenizer_jsconfig.hpp b/operators/tokenizer/tokenizer_jsconfig.hpp
index acb565a2e..cd1a67b59 100644
--- a/operators/tokenizer/tokenizer_jsconfig.hpp
+++ b/operators/tokenizer/tokenizer_jsconfig.hpp
@@ -10,6 +10,30 @@
 
 namespace ort_extensions {
 
+enum class TokenType {
+  kUnknown, kUnigram, kBPE
+};
+
+constexpr std::pair<const char*, TokenType> kTokenizerDict[] = {
+  {"PreTrainedTokenizerFast", TokenType::kBPE},
+  {"CLIPTokenizer", TokenType::kBPE},
+  {"WhisperTokenizer", TokenType::kBPE},
+  {"GemmaTokenizer", TokenType::kBPE},
+  {"LlamaTokenizer", TokenType::kBPE},
+  {"Phi3Tokenizer", TokenType::kBPE},
+  {"CodeLlamaTokenizer", TokenType::kBPE},
+  {"CodeGenTokenizer", TokenType::kBPE},
+  {"GPT2Tokenizer", TokenType::kBPE},
+  {"Qwen2Tokenizer", TokenType::kBPE},
+  {"BaichuanTokenizer", TokenType::kBPE},
+
+  {"", TokenType::kUnigram},
+  {"T5Tokenizer", TokenType::kUnigram},
+  {"ChatGLMTokenizer", TokenType::kUnigram},
+  {"XLMRobertaTokenizer", TokenType::kUnigram}
+};
+
+
 // TokenJsonConfig: Handles loading and parsing of JSON configuration files for tokenizers
 class TokenJsonConfig final {
  public:
@@ -230,6 +254,14 @@ class TokenJsonConfig final {
     return added_token;
   }
 
+  static TokenType GetTokenType(const std::string& tok) {
+    static const std::unordered_map<std::string, TokenType> dict {
+        std::begin(kTokenizerDict), std::end(kTokenizerDict) };
+
+    auto iter = dict.find(tok);
+    return iter == dict.end() ? TokenType::kUnknown : iter->second;
+  }
+
  private:
   void LoadAddedTokens(const json& tok_json) {
     auto added_tokens = tok_json.find("added_tokens");
diff --git a/operators/tokenizer/tokenizer_op_impl.hpp b/operators/tokenizer/tokenizer_op_impl.hpp
new file mode 100644
index 000000000..455f88fa5
--- /dev/null
+++ b/operators/tokenizer/tokenizer_op_impl.hpp
@@ -0,0 +1,56 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+#include <variant>
+
+#include "bpe_kernels.h"
+#include "ugm_kernels.hpp"
+
+#include "ext_status.h"
+#include "op_def_struct.h"
+#include "ort_c_to_cpp.h"
+
+namespace ort_extensions {
+
+class JsonTokenizerOpKernel {
+ public:
+  OrtStatusPtr OnModelAttach(const OrtApi& api, const OrtKernelInfo& info) {
+    std::string config_json;
+    ORTW_RETURN_IF_ERROR(OrtW::API::GetOpAttributeString(api, info, "tokenizer_config", config_json));
+
+    std::string vocab_json;
+    ORTW_RETURN_IF_ERROR(OrtW::API::GetOpAttributeString(api, info, "tokenizer_vocab", vocab_json));
+
+    TokenJsonConfig cfg;
+    OrtxTokenizerBlob blob({config_json.c_str(), config_json.length()},
+                           {vocab_json.c_str(), vocab_json.length()});
+
+    ORTX_RETURN_IF_ERROR(cfg.LoadFromBlob(blob));
+
+    auto type = TokenJsonConfig::GetTokenType(cfg.tokenizer_class_);
+    if (type == TokenType::kUnigram) {
+      tokenizer_ = std::make_unique<SpmUgmTokenizer>();
+    } else if (type == TokenType::kBPE) {
+      tokenizer_ = std::make_unique<JsonFastTokenizer>();
+    } else {
+      return OrtxStatus(kOrtxErrorCorruptData, "Unknown tokenizer type");
+    }
+
+    return std::visit([&](auto& ptr) { return ptr->Load(cfg); }, tokenizer_);
+  }
+
+  OrtxStatus Compute(const ortc::Tensor<std::string>& input,
+                     ortc::Tensor<int64_t>& tokenize_output,
+                     std::optional<ortc::Tensor<int64_t>*> attention_mask = std::nullopt,
+                     std::optional<ortc::Tensor<int64_t>*> offset_mapping = std::nullopt) const {
+
+    return std::visit([&](auto& ptr) { 
+        return ptr->Compute(input, tokenize_output, attention_mask, offset_mapping); 
+    }, tokenizer_);
+  }
+
+ private:
+  std::variant<std::unique_ptr<JsonFastTokenizer>, std::unique_ptr<SpmUgmTokenizer>> tokenizer_;
+};
+
+}  // namespace ort_extensions
diff --git a/operators/tokenizer/tokenizers.cc b/operators/tokenizer/tokenizers.cc
index e723a9874..813b09a9f 100644
--- a/operators/tokenizer/tokenizers.cc
+++ b/operators/tokenizer/tokenizers.cc
@@ -7,6 +7,8 @@
 #include "bpe_kernels.h"
 #include "bpe_tokenizer_model.hpp"
 #include "bpe_decoder.hpp"
+#include "tokenizer_op_impl.hpp"
+using namespace ort_extensions;
 #endif
 
 #ifdef ENABLE_SPM_TOKENIZER
@@ -40,6 +42,7 @@ FxLoadCustomOpFactory LoadCustomOpClasses_Tokenizer = []() -> CustomOpArray& {
       CustomCpuStructV2("RobertaTokenizer", RobertaTokenizer),
       CustomCpuStructV2("BpeDecoder", KernelBpeDecoder),
       CustomCpuStructV2("SpmTokenizer", SpmTokenizer),
+      CustomCpuStructV2("HfJsonTokenizer", JsonTokenizerOpKernel),
 #endif
 
 #ifdef ENABLE_SPM_TOKENIZER
diff --git a/operators/tokenizer/trie_tokenizer.hpp b/operators/tokenizer/trie_tokenizer.hpp
index 09aadeaa6..859505cc1 100644
--- a/operators/tokenizer/trie_tokenizer.hpp
+++ b/operators/tokenizer/trie_tokenizer.hpp
@@ -105,7 +105,7 @@ struct KernelTrieTokenizer {
  public:
   OrtStatusPtr OnModelAttach(const OrtApi& api, const OrtKernelInfo& info) {
     std::string text_tokens;
-    ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "vocab", text_tokens));
+    ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "vocab", text_tokens));
     tokenizer = std::make_shared<TrieTokenizer>(text_tokens);
     return nullptr;
   };
@@ -156,7 +156,7 @@ struct KernelTrieDetokenizer {
  public:
   OrtStatusPtr OnModelAttach(const OrtApi& api, const OrtKernelInfo& info) {
     std::string text_tokens;
-    ORTX_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "vocab", text_tokens));
+    ORTW_RETURN_IF_ERROR(OrtW::GetOpAttribute(info, "vocab", text_tokens));
     tokenizer = std::make_shared<TrieTokenizer>(text_tokens);
     return nullptr;
   };
diff --git a/operators/tokenizer/ugm_kernels.hpp b/operators/tokenizer/ugm_kernels.hpp
index dd50ae4e8..b64a1c2a1 100644
--- a/operators/tokenizer/ugm_kernels.hpp
+++ b/operators/tokenizer/ugm_kernels.hpp
@@ -214,7 +214,13 @@ struct SpmUgmTokenizer {
     return std::get<0>(iter->second);
   }
 
-  OrtxStatus Compute(const ortc::Tensor<std::string>& input, ortc::Tensor<int64_t>& tokenize_output) const {
+  OrtxStatus Compute(const ortc::Tensor<std::string>& input, ortc::Tensor<int64_t>& tokenize_output,
+                     std::optional<ortc::Tensor<int64_t>*> attention_mask = std::nullopt,
+                     std::optional<ortc::Tensor<int64_t>*> offset_mapping = std::nullopt) const {
+    if (attention_mask.has_value() || offset_mapping.has_value()) {
+      return {kOrtxErrorInvalidArgument, "attention-mask or offset-mapping was supported in unigram tokenizer"};
+    }
+
     if (input.Shape().size() != 1) {
       return OrtxStatus(extError_t::kOrtxErrorInvalidArgument, "Input tensor must have rank 1.");
     }
diff --git a/test/data/tiktoken/tokenizer_config.json b/test/data/tiktoken/tokenizer_config.json
deleted file mode 100644
index 72193e9eb..000000000
--- a/test/data/tiktoken/tokenizer_config.json
+++ /dev/null
@@ -1,2061 +0,0 @@
-{
-  "added_tokens_decoder": {
-    "128000": {
-      "content": "<|begin_of_text|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128001": {
-      "content": "<|end_of_text|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128002": {
-      "content": "<|reserved_special_token_0|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128003": {
-      "content": "<|reserved_special_token_1|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128004": {
-      "content": "<|reserved_special_token_2|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128005": {
-      "content": "<|reserved_special_token_3|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128006": {
-      "content": "<|start_header_id|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128007": {
-      "content": "<|end_header_id|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128008": {
-      "content": "<|reserved_special_token_4|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128009": {
-      "content": "<|eot_id|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128010": {
-      "content": "<|reserved_special_token_5|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128011": {
-      "content": "<|reserved_special_token_6|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128012": {
-      "content": "<|reserved_special_token_7|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128013": {
-      "content": "<|reserved_special_token_8|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128014": {
-      "content": "<|reserved_special_token_9|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128015": {
-      "content": "<|reserved_special_token_10|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128016": {
-      "content": "<|reserved_special_token_11|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128017": {
-      "content": "<|reserved_special_token_12|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128018": {
-      "content": "<|reserved_special_token_13|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128019": {
-      "content": "<|reserved_special_token_14|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128020": {
-      "content": "<|reserved_special_token_15|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128021": {
-      "content": "<|reserved_special_token_16|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128022": {
-      "content": "<|reserved_special_token_17|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128023": {
-      "content": "<|reserved_special_token_18|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128024": {
-      "content": "<|reserved_special_token_19|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128025": {
-      "content": "<|reserved_special_token_20|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128026": {
-      "content": "<|reserved_special_token_21|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128027": {
-      "content": "<|reserved_special_token_22|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128028": {
-      "content": "<|reserved_special_token_23|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128029": {
-      "content": "<|reserved_special_token_24|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128030": {
-      "content": "<|reserved_special_token_25|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128031": {
-      "content": "<|reserved_special_token_26|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128032": {
-      "content": "<|reserved_special_token_27|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128033": {
-      "content": "<|reserved_special_token_28|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128034": {
-      "content": "<|reserved_special_token_29|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128035": {
-      "content": "<|reserved_special_token_30|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128036": {
-      "content": "<|reserved_special_token_31|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128037": {
-      "content": "<|reserved_special_token_32|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128038": {
-      "content": "<|reserved_special_token_33|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128039": {
-      "content": "<|reserved_special_token_34|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128040": {
-      "content": "<|reserved_special_token_35|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128041": {
-      "content": "<|reserved_special_token_36|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128042": {
-      "content": "<|reserved_special_token_37|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128043": {
-      "content": "<|reserved_special_token_38|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128044": {
-      "content": "<|reserved_special_token_39|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128045": {
-      "content": "<|reserved_special_token_40|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128046": {
-      "content": "<|reserved_special_token_41|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128047": {
-      "content": "<|reserved_special_token_42|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128048": {
-      "content": "<|reserved_special_token_43|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128049": {
-      "content": "<|reserved_special_token_44|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128050": {
-      "content": "<|reserved_special_token_45|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128051": {
-      "content": "<|reserved_special_token_46|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128052": {
-      "content": "<|reserved_special_token_47|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128053": {
-      "content": "<|reserved_special_token_48|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128054": {
-      "content": "<|reserved_special_token_49|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128055": {
-      "content": "<|reserved_special_token_50|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128056": {
-      "content": "<|reserved_special_token_51|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128057": {
-      "content": "<|reserved_special_token_52|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128058": {
-      "content": "<|reserved_special_token_53|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128059": {
-      "content": "<|reserved_special_token_54|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128060": {
-      "content": "<|reserved_special_token_55|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128061": {
-      "content": "<|reserved_special_token_56|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128062": {
-      "content": "<|reserved_special_token_57|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128063": {
-      "content": "<|reserved_special_token_58|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128064": {
-      "content": "<|reserved_special_token_59|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128065": {
-      "content": "<|reserved_special_token_60|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128066": {
-      "content": "<|reserved_special_token_61|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128067": {
-      "content": "<|reserved_special_token_62|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128068": {
-      "content": "<|reserved_special_token_63|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128069": {
-      "content": "<|reserved_special_token_64|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128070": {
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-    "128172": {
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-      "single_word": false,
-      "special": true
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-    "128173": {
-      "content": "<|reserved_special_token_168|>",
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-      "normalized": false,
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-      "single_word": false,
-      "special": true
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-    "128174": {
-      "content": "<|reserved_special_token_169|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128175": {
-      "content": "<|reserved_special_token_170|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128176": {
-      "content": "<|reserved_special_token_171|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128177": {
-      "content": "<|reserved_special_token_172|>",
-      "lstrip": false,
-      "normalized": false,
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-      "single_word": false,
-      "special": true
-    },
-    "128178": {
-      "content": "<|reserved_special_token_173|>",
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-      "special": true
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-    "128179": {
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-      "normalized": false,
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-      "special": true
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-    "128180": {
-      "content": "<|reserved_special_token_175|>",
-      "lstrip": false,
-      "normalized": false,
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-      "single_word": false,
-      "special": true
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-    "128181": {
-      "content": "<|reserved_special_token_176|>",
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-      "special": true
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-    "128182": {
-      "content": "<|reserved_special_token_177|>",
-      "lstrip": false,
-      "normalized": false,
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-      "special": true
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-    "128183": {
-      "content": "<|reserved_special_token_178|>",
-      "lstrip": false,
-      "normalized": false,
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-    "128184": {
-      "content": "<|reserved_special_token_179|>",
-      "lstrip": false,
-      "normalized": false,
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-      "single_word": false,
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-    "128185": {
-      "content": "<|reserved_special_token_180|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
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-    "128186": {
-      "content": "<|reserved_special_token_181|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
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-    "128187": {
-      "content": "<|reserved_special_token_182|>",
-      "lstrip": false,
-      "normalized": false,
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-      "single_word": false,
-      "special": true
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-    "128188": {
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-      "single_word": false,
-      "special": true
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-    "128189": {
-      "content": "<|reserved_special_token_184|>",
-      "lstrip": false,
-      "normalized": false,
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-      "single_word": false,
-      "special": true
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-    "128190": {
-      "content": "<|reserved_special_token_185|>",
-      "lstrip": false,
-      "normalized": false,
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-    "128191": {
-      "content": "<|reserved_special_token_186|>",
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-    "128192": {
-      "content": "<|reserved_special_token_187|>",
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-    "128193": {
-      "content": "<|reserved_special_token_188|>",
-      "lstrip": false,
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-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128194": {
-      "content": "<|reserved_special_token_189|>",
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-      "single_word": false,
-      "special": true
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-    "128195": {
-      "content": "<|reserved_special_token_190|>",
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-    "128196": {
-      "content": "<|reserved_special_token_191|>",
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-    "128197": {
-      "content": "<|reserved_special_token_192|>",
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-    "128198": {
-      "content": "<|reserved_special_token_193|>",
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-    "128199": {
-      "content": "<|reserved_special_token_194|>",
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-    "128200": {
-      "content": "<|reserved_special_token_195|>",
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-      "special": true
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-    "128201": {
-      "content": "<|reserved_special_token_196|>",
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-      "content": "<|reserved_special_token_197|>",
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-    },
-    "128203": {
-      "content": "<|reserved_special_token_198|>",
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-    "128204": {
-      "content": "<|reserved_special_token_199|>",
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-    "128205": {
-      "content": "<|reserved_special_token_200|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
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-    "128206": {
-      "content": "<|reserved_special_token_201|>",
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-      "single_word": false,
-      "special": true
-    },
-    "128207": {
-      "content": "<|reserved_special_token_202|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128208": {
-      "content": "<|reserved_special_token_203|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128209": {
-      "content": "<|reserved_special_token_204|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128210": {
-      "content": "<|reserved_special_token_205|>",
-      "lstrip": false,
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-      "content": "<|reserved_special_token_206|>",
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-    },
-    "128212": {
-      "content": "<|reserved_special_token_207|>",
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-      "content": "<|reserved_special_token_208|>",
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-    "128214": {
-      "content": "<|reserved_special_token_209|>",
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-    "128215": {
-      "content": "<|reserved_special_token_210|>",
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-    "128216": {
-      "content": "<|reserved_special_token_211|>",
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-      "content": "<|reserved_special_token_212|>",
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-    "128218": {
-      "content": "<|reserved_special_token_213|>",
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-      "content": "<|reserved_special_token_214|>",
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-      "content": "<|reserved_special_token_215|>",
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-    "128221": {
-      "content": "<|reserved_special_token_216|>",
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-      "special": true
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-    "128223": {
-      "content": "<|reserved_special_token_218|>",
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-    "128224": {
-      "content": "<|reserved_special_token_219|>",
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-    "128225": {
-      "content": "<|reserved_special_token_220|>",
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-    "128226": {
-      "content": "<|reserved_special_token_221|>",
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-    "128227": {
-      "content": "<|reserved_special_token_222|>",
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-      "single_word": false,
-      "special": true
-    },
-    "128228": {
-      "content": "<|reserved_special_token_223|>",
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-      "special": true
-    },
-    "128229": {
-      "content": "<|reserved_special_token_224|>",
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-      "single_word": false,
-      "special": true
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-    "128230": {
-      "content": "<|reserved_special_token_225|>",
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-      "single_word": false,
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-    "128231": {
-      "content": "<|reserved_special_token_226|>",
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-      "single_word": false,
-      "special": true
-    },
-    "128232": {
-      "content": "<|reserved_special_token_227|>",
-      "lstrip": false,
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-      "single_word": false,
-      "special": true
-    },
-    "128233": {
-      "content": "<|reserved_special_token_228|>",
-      "lstrip": false,
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-      "single_word": false,
-      "special": true
-    },
-    "128234": {
-      "content": "<|reserved_special_token_229|>",
-      "lstrip": false,
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-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128235": {
-      "content": "<|reserved_special_token_230|>",
-      "lstrip": false,
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-      "single_word": false,
-      "special": true
-    },
-    "128236": {
-      "content": "<|reserved_special_token_231|>",
-      "lstrip": false,
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-      "single_word": false,
-      "special": true
-    },
-    "128237": {
-      "content": "<|reserved_special_token_232|>",
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-      "single_word": false,
-      "special": true
-    },
-    "128238": {
-      "content": "<|reserved_special_token_233|>",
-      "lstrip": false,
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-      "single_word": false,
-      "special": true
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-    "128239": {
-      "content": "<|reserved_special_token_234|>",
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-      "special": true
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-    "128240": {
-      "content": "<|reserved_special_token_235|>",
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-      "single_word": false,
-      "special": true
-    },
-    "128241": {
-      "content": "<|reserved_special_token_236|>",
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-      "special": true
-    },
-    "128242": {
-      "content": "<|reserved_special_token_237|>",
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-      "single_word": false,
-      "special": true
-    },
-    "128243": {
-      "content": "<|reserved_special_token_238|>",
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-    "128244": {
-      "content": "<|reserved_special_token_239|>",
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-    "128245": {
-      "content": "<|reserved_special_token_240|>",
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-      "single_word": false,
-      "special": true
-    },
-    "128246": {
-      "content": "<|reserved_special_token_241|>",
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-      "single_word": false,
-      "special": true
-    },
-    "128247": {
-      "content": "<|reserved_special_token_242|>",
-      "lstrip": false,
-      "normalized": false,
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-      "single_word": false,
-      "special": true
-    },
-    "128248": {
-      "content": "<|reserved_special_token_243|>",
-      "lstrip": false,
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-      "single_word": false,
-      "special": true
-    },
-    "128249": {
-      "content": "<|reserved_special_token_244|>",
-      "lstrip": false,
-      "normalized": false,
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-      "single_word": false,
-      "special": true
-    },
-    "128250": {
-      "content": "<|reserved_special_token_245|>",
-      "lstrip": false,
-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    },
-    "128251": {
-      "content": "<|reserved_special_token_246|>",
-      "lstrip": false,
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-      "single_word": false,
-      "special": true
-    },
-    "128252": {
-      "content": "<|reserved_special_token_247|>",
-      "lstrip": false,
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-      "single_word": false,
-      "special": true
-    },
-    "128253": {
-      "content": "<|reserved_special_token_248|>",
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-      "single_word": false,
-      "special": true
-    },
-    "128254": {
-      "content": "<|reserved_special_token_249|>",
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-      "single_word": false,
-      "special": true
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-    "128255": {
-      "content": "<|reserved_special_token_250|>",
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-      "normalized": false,
-      "rstrip": false,
-      "single_word": false,
-      "special": true
-    }
-  },
-  "bos_token": "<|begin_of_text|>",
-  "clean_up_tokenization_spaces": true,
-  "eos_token": "<|end_of_text|>",
-  "model_input_names": [
-    "input_ids",
-    "attention_mask"
-  ],
-  "model_max_length": 1000000000000000019884624838656,
-  "tokenizer_class": "PreTrainedTokenizerFast"
-}
diff --git a/test/data/tiktoken/tokenizer.json b/test/data/tokenizer/llama3_test.onnx
similarity index 99%
rename from test/data/tiktoken/tokenizer.json
rename to test/data/tokenizer/llama3_test.onnx
index b197f72ef..847e00f07 100644
--- a/test/data/tiktoken/tokenizer.json
+++ b/test/data/tokenizer/llama3_test.onnx
@@ -1,4 +1,2069 @@
-{
+:�ҭ
+�ҭ
+stridsHfJsonTokenizer_1"HfJsonTokenizer*��
+tokenizer_config"��{
+  "added_tokens_decoder": {
+    "128000": {
+      "content": "<|begin_of_text|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128001": {
+      "content": "<|end_of_text|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128002": {
+      "content": "<|reserved_special_token_0|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128003": {
+      "content": "<|reserved_special_token_1|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128004": {
+      "content": "<|reserved_special_token_2|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128005": {
+      "content": "<|reserved_special_token_3|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128006": {
+      "content": "<|start_header_id|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128007": {
+      "content": "<|end_header_id|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128008": {
+      "content": "<|reserved_special_token_4|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128009": {
+      "content": "<|eot_id|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128010": {
+      "content": "<|reserved_special_token_5|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+    "128212": {
+      "content": "<|reserved_special_token_207|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128213": {
+      "content": "<|reserved_special_token_208|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128214": {
+      "content": "<|reserved_special_token_209|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128215": {
+      "content": "<|reserved_special_token_210|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128216": {
+      "content": "<|reserved_special_token_211|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128217": {
+      "content": "<|reserved_special_token_212|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128218": {
+      "content": "<|reserved_special_token_213|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128219": {
+      "content": "<|reserved_special_token_214|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128220": {
+      "content": "<|reserved_special_token_215|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128221": {
+      "content": "<|reserved_special_token_216|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128222": {
+      "content": "<|reserved_special_token_217|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128223": {
+      "content": "<|reserved_special_token_218|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128224": {
+      "content": "<|reserved_special_token_219|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128225": {
+      "content": "<|reserved_special_token_220|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128226": {
+      "content": "<|reserved_special_token_221|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128227": {
+      "content": "<|reserved_special_token_222|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128228": {
+      "content": "<|reserved_special_token_223|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128229": {
+      "content": "<|reserved_special_token_224|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128230": {
+      "content": "<|reserved_special_token_225|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128231": {
+      "content": "<|reserved_special_token_226|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128232": {
+      "content": "<|reserved_special_token_227|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128233": {
+      "content": "<|reserved_special_token_228|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128234": {
+      "content": "<|reserved_special_token_229|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128235": {
+      "content": "<|reserved_special_token_230|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128236": {
+      "content": "<|reserved_special_token_231|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128237": {
+      "content": "<|reserved_special_token_232|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128238": {
+      "content": "<|reserved_special_token_233|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128239": {
+      "content": "<|reserved_special_token_234|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128240": {
+      "content": "<|reserved_special_token_235|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128241": {
+      "content": "<|reserved_special_token_236|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128242": {
+      "content": "<|reserved_special_token_237|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128243": {
+      "content": "<|reserved_special_token_238|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128244": {
+      "content": "<|reserved_special_token_239|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128245": {
+      "content": "<|reserved_special_token_240|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128246": {
+      "content": "<|reserved_special_token_241|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128247": {
+      "content": "<|reserved_special_token_242|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128248": {
+      "content": "<|reserved_special_token_243|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128249": {
+      "content": "<|reserved_special_token_244|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128250": {
+      "content": "<|reserved_special_token_245|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128251": {
+      "content": "<|reserved_special_token_246|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128252": {
+      "content": "<|reserved_special_token_247|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128253": {
+      "content": "<|reserved_special_token_248|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128254": {
+      "content": "<|reserved_special_token_249|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128255": {
+      "content": "<|reserved_special_token_250|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|begin_of_text|>",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|end_of_text|>",
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 1000000000000000019884624838656,
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}
+�
*�ƪ
+tokenizer_vocab"�ƪ{
   "version": "1.0",
   "truncation": null,
   "padding": null,
@@ -410560,4 +412625,13 @@
       "éĶ ¦"
     ]
   }
-}
\ No newline at end of file
+}�
:ai.onnx.contribog_HfJsonTokenizer_2Z
+str
+	
+
Nb
+ids
+
+
N
+B
+ai.onnxB
+ai.onnx.contrib

\ No newline at end of file
diff --git a/test/pp_api_test/test_tokenizer.cc b/test/pp_api_test/test_tokenizer.cc
index ec7e45dbf..527d832cc 100644
--- a/test/pp_api_test/test_tokenizer.cc
+++ b/test/pp_api_test/test_tokenizer.cc
@@ -27,7 +27,7 @@ TEST(CApiTest, ApiTest) {
   int ver = OrtxGetAPIVersion();
   EXPECT_GT(ver, 0);
   OrtxTokenizer* tokenizer = NULL;
-  extError_t err = OrtxCreateTokenizer(&tokenizer, "data/tiktoken");
+  extError_t err = OrtxCreateTokenizer(&tokenizer, "data/llama2");
   EXPECT_EQ(err, kOrtxOK);
 
   const char* input = "This is a test";
@@ -203,34 +203,6 @@ TEST(OrtxTokenizerTest, ClipTokenizer) {
   EXPECT_EQ(out_text[0], input[0]);
 }
 
-TEST(OrtxTokenizerTest, TicTokenTokenizer) {
-  auto tokenizer = std::make_unique<ort_extensions::TokenizerImpl>();
-  auto status = tokenizer->Load("data/tiktoken");
-  if (!status.IsOk()) {
-    std::cout << status.ToString() << std::endl;
-    tokenizer.reset();
-  }
-
-  // validate tokenizer is not null
-    ASSERT_NE(tokenizer.get(), nullptr) << "Tokenizer is null, stopping the test.";
-
-  std::vector<extTokenId_t> EXPECTED_IDS_0 = {128000, 2028, 374, 264, 1296};
-  std::vector<std::string_view> input = {"This is a test", "the second one"};
-
-  std::vector<std::vector<extTokenId_t>> token_ids;
-  status = tokenizer->Tokenize(input, token_ids);
-  EXPECT_TRUE(status.IsOk());
-  EXPECT_EQ(token_ids.size(), 2);
-  EXPECT_EQ(token_ids[0], EXPECTED_IDS_0);
-  EXPECT_EQ(token_ids[1].size(), 4);
-
-  std::vector<std::string> out_text;
-  std::vector<ort_extensions::span<extTokenId_t const>> token_ids_span = {token_ids[0], token_ids[1]};
-  status = tokenizer->Detokenize(token_ids_span, out_text);
-  EXPECT_TRUE(status.IsOk());
-  EXPECT_EQ(out_text[0], input[0]);
-}
-
 TEST(OrtxTokenizerTest, Phi3_Small_Hf_Tokenizer) {
   auto tokenizer = std::make_unique<ort_extensions::TokenizerImpl>();
   auto status = tokenizer->Load("data/tokenizer/phi-3-small-cvt");
diff --git a/test/shared_test/test_ortops.cc b/test/shared_test/test_ortops.cc
index be981cc43..9534c9e6b 100644
--- a/test/shared_test/test_ortops.cc
+++ b/test/shared_test/test_ortops.cc
@@ -175,9 +175,7 @@ template <typename T>
 void _assert_eq(Ort::Value& output_tensor, const std::vector<T>& expected, size_t total_len) {
   ASSERT_EQ(expected.size(), total_len);
   T* f = output_tensor.GetTensorMutableData<T>();
-  for (size_t i = 0; i != total_len; ++i) {
-    ASSERT_EQ(expected[i], f[i]);
-  }
+  ASSERT_EQ(expected, std::vector<T>(f, f + total_len));
 }
 
 void GetTensorMutableDataString(const OrtApi& api, const OrtValue* value, std::vector<std::string>& output) {
diff --git a/test/shared_test/test_ortops_tokenizer.cc b/test/shared_test/test_ortops_tokenizer.cc
index cf5228bd3..08ceb34e3 100644
--- a/test/shared_test/test_ortops_tokenizer.cc
+++ b/test/shared_test/test_ortops_tokenizer.cc
@@ -8,7 +8,7 @@
 #include "test_kernel.hpp"
 
 
-TEST(tokenizer_opertors, test_bert_tokenizer) {
+TEST(tokenizer_operators, test_bert_tokenizer) {
   auto ort_env = std::make_unique<Ort::Env>(ORT_LOGGING_LEVEL_WARNING, "Default");
 
   std::vector<TestValue> inputs(1);
@@ -417,4 +417,24 @@ TEST(tokenizer_opertors, test_bert_tokenizer_decoder_with_idices) {
   outputs[0].dims = {1};
   outputs[0].values_string = {"ZheJiuShisuibianDaDePinYing, YongLaiCeshiSuffixCase"};
   TestInference(*ort_env, model_path.c_str(), inputs, outputs);
-}
\ No newline at end of file
+}
+
+TEST(tokenizer_operators, test_hf_json_tokenizer) {
+  auto ort_env = std::make_unique<Ort::Env>(ORT_LOGGING_LEVEL_WARNING, "Default");
+
+  std::vector<TestValue> inputs(1);
+  inputs[0].name = "str";
+  inputs[0].element_type = ONNXTensorElementDataType::ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING;
+  inputs[0].dims = {1};
+  inputs[0].values_string = {"We look forward to welcoming you to our stores. Whether you shop in a store or shop online, our Specialists can help you buy the products you love."};
+
+  std::vector<TestValue> outputs(1);
+  outputs[0].name = "ids";
+  outputs[0].element_type = ONNXTensorElementDataType::ONNX_TENSOR_ELEMENT_DATA_TYPE_INT64;
+  outputs[0].dims = {1, 32};
+  outputs[0].values_int64 = {128000, 1687, 1427, 4741, 311, 36387, 499, 311, 1057, 10756, 13, 13440, 499, 8221, 304, 264, 3637, 477, 8221, 2930, 11, 1057, 92794, 649, 1520, 499, 3780, 279, 3956, 499, 3021, 13};
+
+  std::filesystem::path model_path = "data";
+  model_path /= "tokenizer/llama3_test.onnx";
+  TestInference(*ort_env, model_path.c_str(), inputs, outputs);
+}
diff --git a/test/test_embedded_tokenizer.py b/test/test_embedded_tokenizer.py
new file mode 100644
index 000000000..257123e20
--- /dev/null
+++ b/test/test_embedded_tokenizer.py
@@ -0,0 +1,43 @@
+# Copyright (c) Microsoft Corporation.
+# Licensed under the MIT License.
+import unittest
+
+import numpy as np
+from transformers import AutoTokenizer, GPT2Tokenizer
+from onnxruntime_extensions import OrtPyFunction, gen_processing_models, ort_inference
+
+
+class TestEmbeddedTokenizer(unittest.TestCase):
+    def test_clip_tokenizer(self):
+        tokenizer = AutoTokenizer.from_pretrained(
+            "openai/clip-vit-base-patch32", use_fast=False)
+        text = """
+               1. Testing long text with multiple lines to check newline handling
+               2. As well as words with apostrophes such as you're, i'm, don't, etc.
+               3. And weird characters such as . , ~ ? ( ) " [ ] ! : - .
+               """
+        ids = tokenizer.encode(text, return_tensors="np")
+
+        ort_tok = OrtPyFunction.from_model(gen_processing_models(
+            tokenizer,
+            pre_kwargs={"WITH_DEFAULT_INPUTS": True})[0],
+            schema_v2=True)
+        actual_ids = ort_tok([text])[0]
+        np.testing.assert_array_equal(ids, actual_ids)
+
+    def test_gpt2_tokenizer(self):
+        tokenizer = GPT2Tokenizer.from_pretrained(
+            "Xenova/gpt-4", use_fast=False)
+        text = "Testing words with apostrophes such as you're, i'm, don't, etc."
+        ids = tokenizer.encode(text, return_tensors="np")
+
+        ort_tok = OrtPyFunction.from_model(gen_processing_models(
+            tokenizer,
+            pre_kwargs={"WITH_DEFAULT_INPUTS": True})[0],
+            schema_v2=True)
+        actual_ids = ort_tok([text])[0]
+        np.testing.assert_array_equal(ids, actual_ids)
+
+
+if __name__ == '__main__':
+    unittest.main()
\ No newline at end of file