diff --git a/eland/ml/pytorch/nlp_ml_model.py b/eland/ml/pytorch/nlp_ml_model.py
index 739ca45..dc5e055 100644
--- a/eland/ml/pytorch/nlp_ml_model.py
+++ b/eland/ml/pytorch/nlp_ml_model.py
@@ -108,6 +108,28 @@ class NlpBertTokenizationConfig(NlpTokenizationConfig):
         self.do_lower_case = do_lower_case
 
 
+class NlpBertJapaneseTokenizationConfig(NlpTokenizationConfig):
+    def __init__(
+        self,
+        *,
+        do_lower_case: t.Optional[bool] = None,
+        with_special_tokens: t.Optional[bool] = None,
+        max_sequence_length: t.Optional[int] = None,
+        truncate: t.Optional[
+            t.Union["t.Literal['first', 'none', 'second']", str]
+        ] = None,
+        span: t.Optional[int] = None,
+    ):
+        super().__init__(
+            configuration_type="bert_ja",
+            with_special_tokens=with_special_tokens,
+            max_sequence_length=max_sequence_length,
+            truncate=truncate,
+            span=span,
+        )
+        self.do_lower_case = do_lower_case
+
+
 class NlpMPNetTokenizationConfig(NlpTokenizationConfig):
     def __init__(
         self,
diff --git a/eland/ml/pytorch/transformers.py b/eland/ml/pytorch/transformers.py
index 742e42c..4f1e312 100644
--- a/eland/ml/pytorch/transformers.py
+++ b/eland/ml/pytorch/transformers.py
@@ -43,6 +43,7 @@ from transformers import (
 from eland.ml.pytorch.nlp_ml_model import (
     FillMaskInferenceOptions,
     NerInferenceOptions,
+    NlpBertJapaneseTokenizationConfig,
     NlpBertTokenizationConfig,
     NlpMPNetTokenizationConfig,
     NlpRobertaTokenizationConfig,
@@ -99,6 +100,7 @@ TASK_TYPE_TO_INFERENCE_CONFIG = {
 SUPPORTED_TASK_TYPES_NAMES = ", ".join(sorted(SUPPORTED_TASK_TYPES))
 SUPPORTED_TOKENIZERS = (
     transformers.BertTokenizer,
+    transformers.BertJapaneseTokenizer,
     transformers.MPNetTokenizer,
     transformers.DPRContextEncoderTokenizer,
     transformers.DPRQuestionEncoderTokenizer,
@@ -684,12 +686,25 @@ class TransformerModel:
                 ).get(self._model_id),
             )
         else:
-            return NlpBertTokenizationConfig(
-                do_lower_case=getattr(self._tokenizer, "do_lower_case", None),
-                max_sequence_length=getattr(
-                    self._tokenizer, "max_model_input_sizes", dict()
-                ).get(self._model_id),
-            )
+            japanese_morphological_tokenizers = ["mecab"]
+            if (
+                hasattr(self._tokenizer, "word_tokenizer_type")
+                and self._tokenizer.word_tokenizer_type
+                in japanese_morphological_tokenizers
+            ):
+                return NlpBertJapaneseTokenizationConfig(
+                    do_lower_case=getattr(self._tokenizer, "do_lower_case", None),
+                    max_sequence_length=getattr(
+                        self._tokenizer, "max_model_input_sizes", dict()
+                    ).get(self._model_id),
+                )
+            else:
+                return NlpBertTokenizationConfig(
+                    do_lower_case=getattr(self._tokenizer, "do_lower_case", None),
+                    max_sequence_length=getattr(
+                        self._tokenizer, "max_model_input_sizes", dict()
+                    ).get(self._model_id),
+                )
 
     def _create_config(
         self, es_version: Optional[Tuple[int, int, int]]