diff --git a/pgml-extension/examples/embedding.sql b/pgml-extension/examples/embedding.sql
new file mode 100644
index 000000000..4e6c5968d
--- /dev/null
+++ b/pgml-extension/examples/embedding.sql
@@ -0,0 +1,7 @@
+\timing on
+
+SELECT pgml.embed('Alibaba-NLP/gte-base-en-v1.5', 'hi mom', '{"trust_remote_code": true}');
+SELECT pgml.embed('Alibaba-NLP/gte-base-en-v1.5', 'hi mom', '{"device": "cuda", "trust_remote_code": true}');
+SELECT pgml.embed('Alibaba-NLP/gte-base-en-v1.5', 'hi mom', '{"device": "cpu", "trust_remote_code": true}');
+SELECT pgml.embed('hkunlp/instructor-xl', 'hi mom', '{"instruction": "Encode it with love"}');
+SELECT pgml.embed('mixedbread-ai/mxbai-embed-large-v1', 'test', '{"prompt": "test prompt: "}');
diff --git a/pgml-extension/examples/image_classification.sql b/pgml-extension/examples/image_classification.sql
index f9a7888a6..24e363e4a 100644
--- a/pgml-extension/examples/image_classification.sql
+++ b/pgml-extension/examples/image_classification.sql
@@ -66,7 +66,7 @@ SELECT * FROM pgml.train('Handwritten Digits', algorithm => 'xgboost', hyperpara
 
 -- runtimes
 SELECT * FROM pgml.train('Handwritten Digits', algorithm => 'linear', runtime => 'python');
-SELECT * FROM pgml.train('Handwritten Digits', algorithm => 'linear', runtime => 'rust');
+--SELECT * FROM pgml.train('Handwritten Digits', algorithm => 'linear', runtime => 'rust');
 
 --SELECT * FROM pgml.train('Handwritten Digits', algorithm => 'xgboost', runtime => 'python', hyperparams => '{"n_estimators": 10}'); -- too slow
 SELECT * FROM pgml.train('Handwritten Digits', algorithm => 'xgboost', runtime => 'rust', hyperparams => '{"n_estimators": 10}');
diff --git a/pgml-extension/src/bindings/transformers/transformers.py b/pgml-extension/src/bindings/transformers/transformers.py
index baa2c2500..ea2df12b9 100644
--- a/pgml-extension/src/bindings/transformers/transformers.py
+++ b/pgml-extension/src/bindings/transformers/transformers.py
@@ -527,8 +527,8 @@ def rank(transformer, query, documents, kwargs):
     return rank_using(model, query, documents, kwargs)
 
 
-def create_embedding(transformer):
-    return SentenceTransformer(transformer)
+def create_embedding(transformer, kwargs):
+    return SentenceTransformer(transformer, **kwargs)
 
 
 def embed_using(model, transformer, inputs, kwargs):
@@ -545,16 +545,32 @@ def embed_using(model, transformer, inputs, kwargs):
 
 def embed(transformer, inputs, kwargs):
     kwargs = orjson.loads(kwargs)
-
     ensure_device(kwargs)
 
+    init_kwarg_keys = [
+        "device",
+        "trust_remote_code",
+        "revision",
+        "model_kwargs",
+        "tokenizer_kwargs",
+        "config_kwargs",
+        "truncate_dim",
+        "token",
+    ]
+    init_kwargs = {
+        key: value for key, value in kwargs.items() if key in init_kwarg_keys
+    }
+    encode_kwargs = {
+        key: value for key, value in kwargs.items() if key not in init_kwarg_keys
+    }
+
     if transformer not in __cache_sentence_transformer_by_name:
         __cache_sentence_transformer_by_name[transformer] = create_embedding(
-            transformer
+            transformer, init_kwargs
         )
     model = __cache_sentence_transformer_by_name[transformer]
 
-    return embed_using(model, transformer, inputs, kwargs)
+    return embed_using(model, transformer, inputs, encode_kwargs)
 
 
 def clear_gpu_cache(memory_usage: None):
diff --git a/pgml-extension/tests/test.sql b/pgml-extension/tests/test.sql
index 2256e0ca4..10ffb4339 100644
--- a/pgml-extension/tests/test.sql
+++ b/pgml-extension/tests/test.sql
@@ -31,5 +31,6 @@ SELECT pgml.load_dataset('wine');
 \i examples/vectors.sql
 \i examples/chunking.sql
 \i examples/preprocessing.sql
+\i examples/embedding.sql
 -- transformers are generally too slow to run in the test suite
 --\i examples/transformers.sql