diff --git a/README.md b/README.md
index 54b2ac4..84a0406 100644
--- a/README.md
+++ b/README.md
@@ -63,7 +63,13 @@ The path to local checkpoint, defaults to None.
 ***tokenizer***: *object*
 
 The method to tokenize input text, defaults to None.
-If None, the operator will use default tokenizer by `model_name` from Huggingface transformers.
+If None, the operator will use default tokenizer by `model_name` from HuggingFace transformers.
+
+
+***return_usage***: *bool*
+
+The flag to return token usage with __call__ method, defaults to False.
+If True, __call__ method will return a dictionary containing data (embedding).
 
 <br />
 
diff --git a/auto_transformers.py b/auto_transformers.py
index b49d841..dd90f30 100644
--- a/auto_transformers.py
+++ b/auto_transformers.py
@@ -107,8 +107,10 @@ class AutoTransformers(NNOperator):
                  tokenizer: object = None,
                  pool: str = 'mean',
                  device: str = None,
+                 return_usage: bool = False
                  ):
         super().__init__()
+        self.return_usage = return_usage
         if pool not in ['mean', 'cls']:
             log.warning('Invalid pool %s, using mean pooling instead.', pool)
             pool = 'mean'
@@ -152,6 +154,8 @@ class AutoTransformers(NNOperator):
         except Exception as e:
             log.error(f'Invalid input for the model: {self.model_name}')
             raise e
+        
+        num_tokens = outs.size(1)
         if self.pool == 'mean':
             outs = self.mean_pool(outs, inputs)
         elif self.pool == 'cls':
@@ -161,6 +165,9 @@ class AutoTransformers(NNOperator):
             features = features.squeeze(0)
         else:
             features = list(features)
+
+        if self.return_usage:
+            return {'data': features, 'token_usage': num_tokens}
         return features
 
     @property