diff --git a/examples/CMakeLists.txt b/examples/CMakeLists.txt
index 60c613d4..db7d5f41 100644
--- a/examples/CMakeLists.txt
+++ b/examples/CMakeLists.txt
@@ -44,6 +44,7 @@ macro(func_vlm_add_executable target)
         ${PROJECT_SOURCE_DIR}/src/tokenizers/Unicode.cpp
         ${PROJECT_SOURCE_DIR}/src/tokenizers/UnicodeData.cpp
         ${PROJECT_SOURCE_DIR}/src/tokenizers/BPE/Bpe.cpp
+        ${PROJECT_SOURCE_DIR}/src/tokenizers/WordPiece/WordPiece.cpp
         ${PROJECT_SOURCE_DIR}/src/processor/PreProcess.cpp
         ${DIR_SRC_PROCESSOE}
         ${DIR_THIRDPARTY_AUDIO}
diff --git a/examples/demo_bert.cpp b/examples/demo_bert.cpp
index dd4397bd..b21281df 100644
--- a/examples/demo_bert.cpp
+++ b/examples/demo_bert.cpp
@@ -25,14 +25,12 @@ int main(int argc, char *argv[]) {
 
     BertTokenizer tokenizer(vocab_path, true);
     string text = "Help me set an alarm at 21:30";
-    auto [token_ids, type_ids, position_ids] = tokenizer.process(text);
-    // token_ids.printData<float>();
-
+    auto inputs = tokenizer.tokenizes(text);
     auto config = BertConfig();
     auto model = BertModel(config);
     model.load(model_path);
 
-    auto res = model({token_ids, type_ids, position_ids})[0];
+    auto res = model({inputs[0], inputs[1], inputs[2]})[0];
 
     res.printData<float>();
 
diff --git a/src/models/bert/modeling_bert.hpp b/src/models/bert/modeling_bert.hpp
index e7d6730f..adb34437 100644
--- a/src/models/bert/modeling_bert.hpp
+++ b/src/models/bert/modeling_bert.hpp
@@ -39,9 +39,7 @@ class BertLayer : public Module {
     BertLayer() = default;
     BertLayer(const BertConfig &config, const string &base_name) {
         // base_name: encoder.layer.n.
-        attention = MultiHeadAttention(config.hidden_size, config.num_attention_heads, config.num_attention_heads,
-                                       config.hidden_size / config.num_attention_heads, SPLIT_NONE, false, false, RoPEType::NONE, -1, -1, 0, false, true, config.names_config,
-                                       base_name + config.names_config._attn_base_name);
+        attention = MultiHeadAttention(config.hidden_size, config.num_attention_heads, config.num_attention_heads, config.hidden_size / config.num_attention_heads, SPLIT_NONE, false, false, RoPEType::NONE, -1, -1, 0, false, true, config.names_config, base_name + config.names_config._attn_base_name);
 
         feed_forward = FeedForward(config.hidden_size, config.intermediate_size,
                                    config.hidden_act, true, config.names_config, base_name);
@@ -55,15 +53,10 @@ class BertLayer : public Module {
 
     std::vector<Tensor> Forward(std::vector<Tensor> inputs, std::vector<std::any> args) override {
         auto hidden_states = inputs[0];
-
         auto attn_out = attention({hidden_states, hidden_states, hidden_states})[0];
-
         hidden_states = attn_norm({hidden_states + attn_out});
-
         auto ff_out = feed_forward({hidden_states})[0];
-
         hidden_states = ff_norm({hidden_states + ff_out});
-
         return {hidden_states};
     }
 
diff --git a/src/models/bert/tokenization_bert.hpp b/src/models/bert/tokenization_bert.hpp
index d4d03809..650bf8ce 100644
--- a/src/models/bert/tokenization_bert.hpp
+++ b/src/models/bert/tokenization_bert.hpp
@@ -1,19 +1,14 @@
 #ifndef TOKENIZATION_BERT_HPP
 #define TOKENIZATION_BERT_HPP
 
-#include "tokenizers/BPE/Bpe.hpp"
 #include "tokenizers/Tokenizer.hpp"
-#include "tokenizers/Unicode.hpp"
 #include "tokenizers/WordPiece/WordPiece.hpp"
-#include <algorithm>
-#include <unordered_map>
 
 // unicode
-#include <codecvt>
+#include <vector>
 
 using namespace mllm;
 
-
 class BertTokenizer final : public WordPieceTokenizer {
 public:
     explicit BertTokenizer(const std::string &vocab_file, bool add_special_tokens = true) :
@@ -22,17 +17,12 @@ class BertTokenizer final : public WordPieceTokenizer {
         _add_special_tokens = add_special_tokens;
         this->add_special_tokens({"[PAD]", "[CLS]", "[SEP]", "[MASK]"});
     }
-    std::tuple<Tensor, Tensor, Tensor> process(std::string text){
+    std::vector<Tensor> tokenizes(std::string &text) override {
         if (_add_special_tokens) {
             text = "[CLS] " + text + " [SEP]";
         }
         auto tokens_id = vector<token_id_t>();
         WordPieceTokenizer::tokenize(text, tokens_id, false);
-//        printf("token: ");
-//        for (auto &token_id : tokens_id) {
-//            printf("%d ", token_id);
-//        }
-        printf("\n");
         auto tokens_type = vector<token_id_t>(tokens_id.size(), 0);
         auto position_ids = vector<token_id_t>(tokens_id.size());
         for (size_t i = 0; i < tokens_id.size(); i++) {
@@ -41,8 +31,7 @@ class BertTokenizer final : public WordPieceTokenizer {
         return {
             tokens2Input(tokens_id, "input_tokens"),
             tokens2Input(tokens_type, "input_tokens_type"),
-            tokens2Input(position_ids, "input_position_ids")
-        };
+            tokens2Input(position_ids, "input_position_ids")};
     }
 
 private:
diff --git a/src/tokenizers/Tokenizer.hpp b/src/tokenizers/Tokenizer.hpp
index 3462a24b..10841f04 100644
--- a/src/tokenizers/Tokenizer.hpp
+++ b/src/tokenizers/Tokenizer.hpp
@@ -108,6 +108,9 @@ class Tokenizer {
         this->tokenize(text, tokens_id, bos_flag);
         return tokens2Input(tokens_id);
     }
+    virtual vector<Tensor> tokenizes(std::string &text) {
+        return {tokenize(text)};
+    }
     virtual std::string detokenize(const std::vector<token_id_t> &tokens);
 
     virtual std::pair<std::string, unsigned> detokenize(Tensor &result) {