diff --git a/libs/infinity_emb/infinity_emb/infinity_server.py b/libs/infinity_emb/infinity_emb/infinity_server.py
index 37440ca5..12c0c3ad 100644
--- a/libs/infinity_emb/infinity_emb/infinity_server.py
+++ b/libs/infinity_emb/infinity_emb/infinity_server.py
@@ -159,6 +159,10 @@ async def _models():
                     ),
                     capabilities=engine.capabilities,
                     backend=engine_args.engine.name,
+                    embedding_dtype=engine_args.embedding_dtype.name,
+                    dtype=engine_args.dtype.name,
+                    revision=engine_args.revision,
+                    lengths_via_tokenize=engine_args.lengths_via_tokenize,
                     device=engine_args.device.name,
                 )
             )
diff --git a/libs/infinity_emb/infinity_emb/transformer/acceleration.py b/libs/infinity_emb/infinity_emb/transformer/acceleration.py
index 2ed8f009..c0b88b9e 100644
--- a/libs/infinity_emb/infinity_emb/transformer/acceleration.py
+++ b/libs/infinity_emb/infinity_emb/transformer/acceleration.py
@@ -2,6 +2,7 @@
 from typing import TYPE_CHECKING
 
 from infinity_emb._optional_imports import CHECK_OPTIMUM
+from infinity_emb.primitives import Device
 
 if CHECK_OPTIMUM.is_available:
     from optimum.bettertransformer import (  # type: ignore[import-untyped]
@@ -13,8 +14,23 @@
 
     from transformers import PreTrainedModel  # type: ignore[import-untyped]
 
+    from infinity_emb.args import EngineArgs
+
+
+def to_bettertransformer(
+    model: "PreTrainedModel", engine_args: "EngineArgs", logger: "Logger"
+):
+    if not engine_args.bettertransformer:
+        return model
+
+    if engine_args.device == Device.mps or (
+        hasattr(model, "device") and model.device.type == "mps"
+    ):
+        logger.warning(
+            "BetterTransformer is not available for MPS device. Continue without bettertransformer modeling code."
+        )
+        return model
 
-def to_bettertransformer(model: "PreTrainedModel", logger: "Logger"):
     if os.environ.get("INFINITY_DISABLE_OPTIMUM", False):  # OLD VAR
         logger.warning(
             "DEPRECATED `INFINITY_DISABLE_OPTIMUM` - setting optimizations via BetterTransformer,"
diff --git a/libs/infinity_emb/infinity_emb/transformer/classifier/torch.py b/libs/infinity_emb/infinity_emb/transformer/classifier/torch.py
index 8dc1b433..f5c96da6 100644
--- a/libs/infinity_emb/infinity_emb/transformer/classifier/torch.py
+++ b/libs/infinity_emb/infinity_emb/transformer/classifier/torch.py
@@ -1,7 +1,6 @@
 from infinity_emb._optional_imports import CHECK_TRANSFORMERS
 from infinity_emb.args import EngineArgs
 from infinity_emb.log_handler import logger
-from infinity_emb.primitives import Device
 from infinity_emb.transformer.abstract import BaseClassifer
 from infinity_emb.transformer.acceleration import to_bettertransformer
 
@@ -31,11 +30,11 @@ def __init__(
         if self._pipe.device.type != "cpu":  # and engine_args.dtype == "float16":
             self._pipe.model = self._pipe.model.half()
 
-        if not (engine_args.device == Device.mps or not engine_args.bettertransformer):
-            self._pipe.model = to_bettertransformer(
-                self._pipe.model,
-                logger,
-            )
+        self._pipe.model = to_bettertransformer(
+            self._pipe.model,
+            engine_args,
+            logger,
+        )
 
         self._infinity_tokenizer = AutoTokenizer.from_pretrained(
             engine_args.model_name_or_path,
diff --git a/libs/infinity_emb/infinity_emb/transformer/crossencoder/torch.py b/libs/infinity_emb/infinity_emb/transformer/crossencoder/torch.py
index 49e9de26..e3cc9d53 100644
--- a/libs/infinity_emb/infinity_emb/transformer/crossencoder/torch.py
+++ b/libs/infinity_emb/infinity_emb/transformer/crossencoder/torch.py
@@ -55,11 +55,11 @@ def __init__(self, *, engine_args: EngineArgs):
         self._infinity_tokenizer = copy.deepcopy(self.tokenizer)
         self.model.eval()  # type: ignore
 
-        if not (self._target_device.type == "mps" or not engine_args.bettertransformer):
-            self.model = to_bettertransformer(
-                self.model,  # type: ignore
-                logger,
-            )
+        self.model = to_bettertransformer(
+            self.model,  # type: ignore
+            engine_args,
+            logger,
+        )
 
         if self._target_device.type == "cuda" and engine_args.dtype in [
             Dtype.auto,
diff --git a/libs/infinity_emb/infinity_emb/transformer/embedder/sentence_transformer.py b/libs/infinity_emb/infinity_emb/transformer/embedder/sentence_transformer.py
index c6785351..e28047d1 100644
--- a/libs/infinity_emb/infinity_emb/transformer/embedder/sentence_transformer.py
+++ b/libs/infinity_emb/infinity_emb/transformer/embedder/sentence_transformer.py
@@ -68,11 +68,11 @@ def __init__(self, *, engine_args=EngineArgs):
         self.eval()
         self.engine_args = engine_args
 
-        if not (self.device.type == "mps" or not engine_args.bettertransformer):
-            fm.auto_model = to_bettertransformer(
-                fm.auto_model,
-                logger,
-            )
+        fm.auto_model = to_bettertransformer(
+            fm.auto_model,
+            engine_args,
+            logger,
+        )
 
         if self.device.type == "cuda" and engine_args.dtype in [
             Dtype.auto,
diff --git a/libs/infinity_emb/infinity_emb/transformer/vision/torch_vision.py b/libs/infinity_emb/infinity_emb/transformer/vision/torch_vision.py
index 6c372713..57f51ac5 100644
--- a/libs/infinity_emb/infinity_emb/transformer/vision/torch_vision.py
+++ b/libs/infinity_emb/infinity_emb/transformer/vision/torch_vision.py
@@ -24,16 +24,21 @@ class ClipLikeModel(BaseClipVisionModel):
     def __init__(self, *, engine_args: EngineArgs):
         CHECK_TORCH.mark_required()
         CHECK_TRANSFORMERS.mark_required()
-
         self.model = AutoModel.from_pretrained(
             engine_args.model_name_or_path,
             revision=engine_args.revision,
             trust_remote_code=engine_args.trust_remote_code,
+            # attn_implementation="eager" if engine_args.bettertransformer else None,
         )
         if torch.cuda.is_available():
             self.model = self.model.cuda()
             if engine_args.dtype in (Dtype.float16, Dtype.auto):
                 self.model = self.model.half()
+        # self.model = to_bettertransformer(
+        #     self.model,
+        #     engine_args,
+        #     logger,
+        # )
         self.processor = AutoProcessor.from_pretrained(
             engine_args.model_name_or_path,
             revision=engine_args.revision,