diff --git a/llama_cpp/llama.py b/llama_cpp/llama.py
index 7e9a6af23..4d37bf959 100644
--- a/llama_cpp/llama.py
+++ b/llama_cpp/llama.py
@@ -932,7 +932,8 @@ def generate(
 
                 sample_idx += 1
                 if stopping_criteria is not None and stopping_criteria(
-                    self._input_ids[: sample_idx], self._scores[sample_idx - self.n_tokens, :]
+                    self._input_ids[:sample_idx],
+                    self._scores[sample_idx - self.n_tokens, :],
                 ):
                     return
                 tokens_or_none = yield token
@@ -958,7 +959,11 @@ def generate(
                 )
 
     def create_embedding(
-        self, input: Union[str, List[str]], model: Optional[str] = None
+        self,
+        input: Union[str, List[str]],
+        model: Optional[str] = None,
+        normalize: bool = False,
+        truncate: bool = True,
     ) -> CreateEmbeddingResponse:
         """Embed a string.
 
@@ -975,7 +980,9 @@ def create_embedding(
         # get numeric embeddings
         embeds: Union[List[List[float]], List[List[List[float]]]]
         total_tokens: int
-        embeds, total_tokens = self.embed(input, return_count=True)  # type: ignore
+        embeds, total_tokens = self.embed(
+            input=input, normalize=normalize, truncate=truncate, return_count=True
+        )
 
         # convert to CreateEmbeddingResponse
         data: List[Embedding] = [
@@ -1313,7 +1320,7 @@ def logit_bias_processor(
         if seed is not None:
             self.set_seed(seed)
         else:
-            self.set_seed(random.Random(self._seed).randint(0, 2 ** 32))
+            self.set_seed(random.Random(self._seed).randint(0, 2**32))
 
         finish_reason = "length"
         multibyte_fix = 0
@@ -2054,7 +2061,10 @@ def create_chat_completion_openai_v1(
             stream = kwargs.get("stream", False)  # type: ignore
             assert isinstance(stream, bool)
             if stream:
-                return (ChatCompletionChunk(**chunk) for chunk in self.create_chat_completion(*args, **kwargs))  # type: ignore
+                return (
+                    ChatCompletionChunk(**chunk)
+                    for chunk in self.create_chat_completion(*args, **kwargs)
+                )  # type: ignore
             else:
                 return ChatCompletion(**self.create_chat_completion(*args, **kwargs))  # type: ignore
         except ImportError:
@@ -2314,7 +2324,11 @@ def from_pretrained(
         if additional_files:
             for additonal_file_name in additional_files:
                 # find the additional shard file:
-                matching_additional_files = [file for file in file_list if fnmatch.fnmatch(file, additonal_file_name)]
+                matching_additional_files = [
+                    file
+                    for file in file_list
+                    if fnmatch.fnmatch(file, additonal_file_name)
+                ]
 
                 if len(matching_additional_files) == 0:
                     raise ValueError(