propagate dtype to internal module when loading for inference

unsloth/models/sentence_transformer.py

@@ -702,10 +702,28 @@ class FastSentenceTransformer(FastModel):
                 isinstance(st_device, str) and st_device in ["auto", "sequential"]
             ):
                 st_device = None
+            
+            # this was added because when loading for inference it was defaulting to float32
+            # propagate dtype to model_kwargs, default to "auto"
+            model_kwargs = kwargs.get("model_kwargs", {})
+            model_kwargs["dtype"] = dtype if dtype is not None else "auto"
+            
+            # filter kwargs for SentenceTransformer
+            st_kwargs = {
+                "device": st_device,
+                "trust_remote_code": trust_remote_code,
+                "token": token,
+                "revision": revision,
+                "model_kwargs": model_kwargs,
+            }
+            
+            # add other known kwargs if present
+            known_keys = ["cache_folder", "truncate_dim", "tokenizer_kwargs", "config_kwargs"]
+            for k in known_keys:
+                if k in kwargs:
+                    st_kwargs[k] = kwargs[k]
 
-            st_model = SentenceTransformer(
-                model_name, device = st_device, trust_remote_code = trust_remote_code
-            )
+            st_model = SentenceTransformer(model_name, **st_kwargs)
             return st_model
 
         if "auto_model" not in kwargs: