Add new SentenceTransformer model with an onnx backend

README.md

@@ -106,7 +106,7 @@ Then you can load this model and run inference.
 from sentence_transformers import SentenceTransformer
 
 # Download from the 🤗 Hub
-model = SentenceTransformer("sentence_transformers_model_id")
+model = SentenceTransformer("databio/sbert-encode-cellines-tuned")
 # Run inference
 sentences = [
     'GM12873',

config.json

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "sentence-transformers/all-MiniLM-L6-v2",
+  "_name_or_path": "databio/sbert-encode-cellines-tuned",
   "architectures": [
     "BertModel"
   ],
@@ -19,7 +19,7 @@
   "pad_token_id": 0,
   "position_embedding_type": "absolute",
   "torch_dtype": "float32",
-  "transformers_version": "4.47.0",
+  "transformers_version": "4.46.3",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 30522

config_sentence_transformers.json

@@ -1,7 +1,7 @@
 {
   "__version__": {
     "sentence_transformers": "3.3.1",
-    "transformers": "4.47.0",
+    "transformers": "4.46.3",
     "pytorch": "2.5.1+cu124"
   },
   "prompts": {},

onnx/model.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e4f2dac9604bbad0d2e3171cef63a8aa91da26bbd823dd9a8829ff2fa9265108
+size 90405214