diff --git a/src/fastllm.cpp b/src/fastllm.cpp
index edc699c..01cff72 100644
--- a/src/fastllm.cpp
+++ b/src/fastllm.cpp
@@ -549,7 +549,9 @@ namespace fastllm {
         data.UpdateUnitSize();
         data.Allocate();
         if (dataType == oriDataType) {
-            memcpy(data.cpuData, oriData, data.GetBytes());
+            if (oriData != nullptr) {
+                memcpy(data.cpuData, oriData, data.GetBytes());
+            } 
         } else if (oriDataType == DataType::BFLOAT16
                 && dataType == DataType::FLOAT16) {
             uint16_t *a = (uint16_t*)data.cpuData;
diff --git a/src/model.cpp b/src/model.cpp
index ec8f53f..4b06059 100644
--- a/src/model.cpp
+++ b/src/model.cpp
@@ -287,6 +287,9 @@ namespace fastllm {
                 if (dstType != DataType::FLOAT32) {
                     ErrorInFastLLM("SafeTensorItem.CreateBuffer: unsupport src dtype " + this->dtype + "\n");
                 }
+            } else if (this->dtype == "I64") {
+                printf("skip I64 tensor %s\n", this->tensorName.c_str());
+                return;
             } else {
                 ErrorInFastLLM("SafeTensorItem.CreateBuffer: unsupport src dtype " + this->dtype + "\n");
             }
diff --git a/src/models/bert.cpp b/src/models/bert.cpp
index 4518633..02875a8 100644
--- a/src/models/bert.cpp
+++ b/src/models/bert.cpp
@@ -212,7 +212,17 @@ namespace fastllm {
 
     void BertModel::WarmUp() {
         printf("Warmup...\n");
-        EmbeddingSentence({"1"}, true);
+        int batch = 1, len = 1;
+        std::vector <float> ids = std::vector <float> (batch * len, 0.0f);
+        std::vector <float> seqLens = std::vector <float> (batch, 0.0f);
+        std::vector <float> token_type_ids = std::vector <float> (batch * len, 0.0f);
+        std::vector <float> attention_mask = std::vector <float> (batch * len, -1e10f);
+        std::vector <float> position_ids = std::vector <float> (batch * len, 0.0f);
+        fastllm::Data inputIds = fastllm::Data(fastllm::DataType::FLOAT32, {batch, len}, ids);
+        fastllm::Data attentionMask = fastllm::Data(fastllm::DataType::FLOAT32, {batch, len}, attention_mask);
+        fastllm::Data tokenTypeIds = fastllm::Data(fastllm::DataType::FLOAT32, {batch, len}, token_type_ids);
+        fastllm::Data positionIds = fastllm::Data(fastllm::DataType::FLOAT32, {batch, len}, position_ids);
+        ForwardAll(inputIds, attentionMask, tokenTypeIds, positionIds, true);
 	    printf("finish.\n");
     }