diff --git a/fastembed/rerank/cross_encoder/onnx_text_cross_encoder.py b/fastembed/rerank/cross_encoder/onnx_text_cross_encoder.py
index 0c104432..e1f5fa4b 100644
--- a/fastembed/rerank/cross_encoder/onnx_text_cross_encoder.py
+++ b/fastembed/rerank/cross_encoder/onnx_text_cross_encoder.py
@@ -1,26 +1,15 @@
-from typing import Iterable, Any, Sequence, Optional, Type
-
+from typing import Any, Iterable, Optional, Sequence, Type
 
 import numpy as np
-
-from fastembed.common import OnnxProvider
-from fastembed.rerank.cross_encoder.onnx_text_model import (
-    OnnxCrossEncoderModel,
-    TextRerankerWorker,
-)
-from fastembed.rerank.cross_encoder.text_cross_encoder_base import TextCrossEncoderBase
-from fastembed.common.utils import define_cache_dir
 from loguru import logger
 
 from fastembed.common import OnnxProvider
 from fastembed.common.onnx_model import OnnxOutputContext
 from fastembed.common.utils import define_cache_dir
 from fastembed.rerank.cross_encoder.onnx_text_model import (
-    OnnxCrossEncoderModel,
-    TextRerankerWorker,
-)
-from fastembed.rerank.cross_encoder.text_cross_encoder_base import TextCrossEncoderBase
-
+    OnnxCrossEncoderModel, TextRerankerWorker)
+from fastembed.rerank.cross_encoder.text_cross_encoder_base import \
+    TextCrossEncoderBase
 
 supported_onnx_models = [
     {
@@ -199,7 +188,13 @@ def rerank_pairs(
         batch_size: int = 64,
         **kwargs: Any,
     ) -> Iterable[float]:
-        yield from self._rerank_pairs(pairs=pairs, batch_size=batch_size, **kwargs)
+        yield from self._rerank_pairs(
+            model_name=self._model_dir,
+            cache_dir=self.cache_dir,
+            pairs=pairs,
+            batch_size=batch_size,
+            **kwargs,
+        )
 
     @classmethod
     def _get_worker_class(cls) -> Type[TextRerankerWorker]:
diff --git a/fastembed/rerank/cross_encoder/onnx_text_model.py b/fastembed/rerank/cross_encoder/onnx_text_model.py
index 0ee33b58..cf076cd0 100644
--- a/fastembed/rerank/cross_encoder/onnx_text_model.py
+++ b/fastembed/rerank/cross_encoder/onnx_text_model.py
@@ -1,18 +1,13 @@
 import os
 from multiprocessing import get_all_start_methods
 from pathlib import Path
-from typing import Sequence, Optional, Iterable, Any, Type
+from typing import Any, Iterable, Optional, Sequence, Type
 
 import numpy as np
 from tokenizers import Encoding
 
-from fastembed.common.onnx_model import (
-    EmbeddingWorker,
-    OnnxModel,
-    OnnxOutputContext,
-    OnnxProvider,
-    T,
-)
+from fastembed.common.onnx_model import (EmbeddingWorker, OnnxModel,
+                                         OnnxOutputContext, OnnxProvider, T)
 from fastembed.common.preprocessor_utils import load_tokenizer
 from fastembed.common.utils import iter_batch
 from fastembed.parallel_processor import ParallelWorkerPool
@@ -61,7 +56,9 @@ def _build_onnx_input(self, tokenized_input):
             )
         return inputs
 
-    def onnx_embed(self, query: str, documents: list[str], **kwargs: Any) -> OnnxOutputContext:
+    def onnx_embed(
+        self, query: str, documents: list[str], **kwargs: Any
+    ) -> OnnxOutputContext:
         pairs = [(query, doc) for doc in documents]
         return self.onnx_embed_pairs(pairs, **kwargs)
 
@@ -80,7 +77,9 @@ def _rerank_documents(
         if not hasattr(self, "model") or self.model is None:
             self.load_onnx_model()
         for batch in iter_batch(documents, batch_size):
-            yield from self._post_process_onnx_output(self.onnx_embed(query, batch, **kwargs))
+            yield from self._post_process_onnx_output(
+                self.onnx_embed(query, batch, **kwargs)
+            )
 
     def _rerank_pairs(
         self,
@@ -108,7 +107,9 @@ def _rerank_pairs(
             if not hasattr(self, "model") or self.model is None:
                 self.load_onnx_model()
             for batch in iter_batch(pairs, batch_size):
-                yield from self._post_process_onnx_output(self.onnx_embed_pairs(batch, **kwargs))
+                yield from self._post_process_onnx_output(
+                    self.onnx_embed_pairs(batch, **kwargs)
+                )
         else:
             if parallel == 0:
                 parallel = os.cpu_count()
diff --git a/fastembed/rerank/cross_encoder/text_cross_encoder.py b/fastembed/rerank/cross_encoder/text_cross_encoder.py
index b27bedc7..f77416ff 100644
--- a/fastembed/rerank/cross_encoder/text_cross_encoder.py
+++ b/fastembed/rerank/cross_encoder/text_cross_encoder.py
@@ -1,8 +1,10 @@
 from typing import Any, Iterable, Optional, Sequence, Type
 
 from fastembed.common import OnnxProvider
-from fastembed.rerank.cross_encoder.onnx_text_cross_encoder import OnnxTextCrossEncoder
-from fastembed.rerank.cross_encoder.text_cross_encoder_base import TextCrossEncoderBase
+from fastembed.rerank.cross_encoder.onnx_text_cross_encoder import \
+    OnnxTextCrossEncoder
+from fastembed.rerank.cross_encoder.text_cross_encoder_base import \
+    TextCrossEncoderBase
 
 
 class TextCrossEncoder(TextCrossEncoderBase):
diff --git a/fastembed/rerank/cross_encoder/text_cross_encoder_base.py b/fastembed/rerank/cross_encoder/text_cross_encoder_base.py
index a34b8cd8..81e76b1c 100644
--- a/fastembed/rerank/cross_encoder/text_cross_encoder_base.py
+++ b/fastembed/rerank/cross_encoder/text_cross_encoder_base.py
@@ -1,4 +1,4 @@
-from typing import Iterable, Optional, Any
+from typing import Any, Iterable, Optional
 
 from fastembed.common.model_management import ModelManagement