diff --git a/fastembed/sparse/bm25.py b/fastembed/sparse/bm25.py
index 7bfcac97..1d7ef36c 100644
--- a/fastembed/sparse/bm25.py
+++ b/fastembed/sparse/bm25.py
@@ -92,7 +92,7 @@ class Bm25(SparseTextEmbeddingBase):
         b (float, optional): The b parameter in the BM25 formula. Defines the importance of the document length.
             Defaults to 0.75.
         avg_len (float, optional): The average length of the documents in the corpus. Defaults to 256.0.
-        language (str, optional): Specifies the language for the stemmer.
+        language (str): Specifies the language for the stemmer.
         disable_stemmer (bool): Disable the stemmer.
     Raises:
         ValueError: If the model_name is not in the format <org>/<model> e.g. BAAI/bge-base-en.
@@ -105,16 +105,14 @@ def __init__(
         k: float = 1.2,
         b: float = 0.75,
         avg_len: float = 256.0,
-        language: Optional[str] = "english",
+        language: str = "english",
         token_max_length: int = 40,
         disable_stemmer: bool = False,
         **kwargs,
     ):
         super().__init__(model_name, cache_dir, **kwargs)
 
-        if language is None:
-            language = "english"
-        elif language not in supported_languages:
+        if language not in supported_languages:
             raise ValueError(f"{language} language is not supported")
         else:
             self.language = language
@@ -153,7 +151,7 @@ def list_supported_models(cls) -> list[dict[str, Any]]:
         return supported_bm25_models
 
     @classmethod
-    def _load_stopwords(cls, model_dir: Path, language: Optional[str]) -> list[str]:
+    def _load_stopwords(cls, model_dir: Path, language: str) -> list[str]:
         stopwords_path = model_dir / f"{language}.txt"
         if not stopwords_path.exists():
             return []
@@ -247,10 +245,7 @@ def _stem(self, tokens: list[str]) -> list[str]:
             if len(token) > self.token_max_length:
                 continue
 
-            if self.stemmer:
-                stemmed_token = self.stemmer.stem_word(lower_token)
-            else:
-                stemmed_token = lower_token
+            stemmed_token = self.stemmer.stem_word(lower_token) if self.stemmer else lower_token
 
             if stemmed_token:
                 stemmed_tokens.append(stemmed_token)