Add new SentenceTransformer model with an onnx backend

Hello!

*This pull request has been automatically generated from the [`push_to_hub`](https://sbert.net/docs/package_reference/sentence_transformer/SentenceTransformer.html#sentence_transformers.SentenceTransformer.push_to_hub) method from the Sentence Transformers library.*

## Full Model Architecture:
```
SentenceTransformer(
(0): Transformer({'max_seq_length': 8192, 'do_lower_case': False}) with Transformer model: ORTModelForFeatureExtraction
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': True, 'pooling_mode_mean_tokens': False, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
)
```

## Tip:
Consider testing this pull request before merging by loading the model from this PR with the `revision` argument:
```python
from sentence_transformers import SentenceTransformer

# TODO: Fill in the PR number
pr_number = 2
model = SentenceTransformer(
"redis/langcache-embed-v1",
revision=f"refs/pr/{pr_number}",
backend="onnx",
)

# Verify that everything works as expected
embeddings = model.encode(["The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium."])
print(embeddings.shape)

similarities = model.similarity(embeddings, embeddings)
print(similarities)
```

config.json

@@ -1,5 +1,4 @@
 {
-  "_name_or_path": "Alibaba-NLP/gte-modernbert-base",
   "architectures": [
     "ModernBertModel"
   ],
@@ -36,12 +35,11 @@
   "num_hidden_layers": 22,
   "pad_token_id": 50283,
   "position_embedding_type": "absolute",
-  "reference_compile": true,
   "repad_logits_with_grad": false,
   "sep_token_id": 50282,
   "sparse_pred_ignore_index": -100,
   "sparse_prediction": false,
   "torch_dtype": "float32",
-  "transformers_version": "4.49.0",
+  "transformers_version": "4.51.3",
   "vocab_size": 50368
 }

config_sentence_transformers.json

@@ -1,8 +1,8 @@
 {
   "__version__": {
-    "sentence_transformers": "3.4.1",
-    "transformers": "4.49.0",
-    "pytorch": "2.5.1+cu124"
+    "sentence_transformers": "4.1.0",
+    "transformers": "4.51.3",
+    "pytorch": "2.6.0+cu124"
   },
   "prompts": {},
   "default_prompt_name": null,

onnx/model.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:935ca87f24ea1f7374313cc6498726316214e24aafd14bf4e05bb8d2c31c5150
+size 596472567

tokenizer_config.json

@@ -933,13 +933,20 @@
   "cls_token": "[CLS]",
   "extra_special_tokens": {},
   "mask_token": "[MASK]",
+  "max_length": 8192,
   "model_input_names": [
     "input_ids",
     "attention_mask"
   ],
-  "model_max_length": 1000000000000000019884624838656,
+  "model_max_length": 8192,
+  "pad_to_multiple_of": null,
   "pad_token": "[PAD]",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
   "sep_token": "[SEP]",
+  "stride": 0,
   "tokenizer_class": "PreTrainedTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
   "unk_token": "[UNK]"
 }