diff --git a/combo/predict.py b/combo/predict.py
index 042343781be1367282e832c10b424676c30767fe..9d0b4a62af383f825f746d9fec8494d1c02882bb 100644
--- a/combo/predict.py
+++ b/combo/predict.py
@@ -12,7 +12,7 @@ from overrides import overrides
 
 from combo import data
 from combo.data import sentence2conllu, tokens2conllu, conllu2sentence
-from combo.utils import download, graph, lambo
+from combo.utils import download, graph, lambo_tokenizer
 
 logger = logging.getLogger(__name__)
 
@@ -59,7 +59,7 @@ class COMBO(predictor.Predictor):
 
     def predict(self, sentence: Union[str, List[str], List[List[str]], List[data.Sentence]]):
         if isinstance(sentence, str):
-            if isinstance(self._tokenizer,lambo.LamboTokenizer):
+            if isinstance(self._tokenizer,lambo_tokenizer.LamboTokenizer):
                 segmented = self._tokenizer.segment(sentence)
                 return self.predict(segmented)
             else:
@@ -239,7 +239,7 @@ class COMBO(predictor.Predictor):
     @classmethod
     def with_lambo_tokenizer(cls, model: models.Model,
                              dataset_reader: allen_data.DatasetReader, lambo_model_name : str = 'en'):
-        return cls(model, dataset_reader, lambo.LamboTokenizer(lambo_model_name))
+        return cls(model, dataset_reader, lambo_tokenizer.LamboTokenizer(lambo_model_name))
 
     @classmethod
     def from_pretrained(cls, path: str, tokenizer=tokenizers.SpacyTokenizer(),
diff --git a/combo/utils/lambo.py b/combo/utils/lambo_tokenizer.py
similarity index 100%
rename from combo/utils/lambo.py
rename to combo/utils/lambo_tokenizer.py
diff --git a/docs/prediction.md b/docs/prediction.md
index 25b7df175d10b3e2d5a48ef8aad693e2c2ed5a5c..f6fe5efdd488a9da3f97af76bedc7ab599c7aa0e 100644
--- a/docs/prediction.md
+++ b/docs/prediction.md
@@ -34,10 +34,10 @@ You can use COMBO with the [LAMBO](https://gitlab.clarin-pl.eu/syntactic-tools/l
 ```python
 # Import COMBO and lambo
 from combo.predict import COMBO
-from combo.utils import lambo
+from combo.utils import lambo_tokenizer
 
 # Download models
-nlp = COMBO.from_pretrained("english-bert-base-ud29",tokenizer=lambo.LamboTokenizer("en"))
+nlp = COMBO.from_pretrained("english-bert-base-ud29",tokenizer=lambo_tokenizer.LamboTokenizer("en"))
 sentences = nlp("This is the first sentence. This is the second sentence to parse.")
 ```