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': 512, 'do_lower_case': False}) with Transformer model: ORTModelForFeatureExtraction
(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
(2): Normalize()
)
```

## 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(
"yco/bilingual-embedding-base",
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

@@ -1,21 +1,20 @@
 {
-  "_name_or_path": "dangvantuan/bilingual_impl",
+  "_name_or_path": "yco/bilingual-embedding-base",
   "architectures": [
     "BilingualModel"
   ],
-  "model_type": "xlm-roberta",
+  "attention_probs_dropout_prob": 0.1,
   "auto_map": {
-    "AutoConfig":"dangvantuan/bilingual_impl--config.BilingualConfig",
+    "AutoConfig": "dangvantuan/bilingual_impl--config.BilingualConfig",
     "AutoModel": "dangvantuan/bilingual_impl--modeling.BilingualModel",
     "AutoModelForMaskedLM": "dangvantuan/bilingual_impl--modeling.BilingualForMaskedLM",
     "AutoModelForMultipleChoice": "dangvantuan/bilingual_impl--modeling.BilingualForMultipleChoice",
     "AutoModelForQuestionAnswering": "dangvantuan/bilingual_impl--modeling.BilingualForQuestionAnswering",
     "AutoModelForSequenceClassification": "dangvantuan/bilingual_impl--modeling.BilingualForSequenceClassification",
     "AutoModelForTokenClassification": "dangvantuan/bilingual_impl--modeling.BilingualForTokenClassification"
-  },  
-  "attention_probs_dropout_prob": 0.1,
-  "classifier_dropout": null,
+  },
   "bos_token_id": 0,
+  "classifier_dropout": null,
   "eos_token_id": 2,
   "hidden_act": "gelu",
   "hidden_dropout_prob": 0.1,
@@ -24,13 +23,14 @@
   "intermediate_size": 3072,
   "layer_norm_eps": 1e-05,
   "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
   "num_attention_heads": 12,
   "num_hidden_layers": 12,
   "output_past": true,
   "pad_token_id": 1,
   "position_embedding_type": "absolute",
   "torch_dtype": "float16",
-  "transformers_version": "4.39.1",
+  "transformers_version": "4.48.0",
   "type_vocab_size": 1,
   "use_cache": true,
   "vocab_size": 250002

config_sentence_transformers.json

@@ -1,9 +1,10 @@
 {
   "__version__": {
-    "sentence_transformers": "2.7.0",
-    "transformers": "4.38.2",
-    "pytorch": "2.2.1+cu121"
+    "sentence_transformers": "4.0.2",
+    "transformers": "4.48.0",
+    "pytorch": "2.3.1"
   },
   "prompts": {},
-  "default_prompt_name": null
+  "default_prompt_name": null,
+  "similarity_fn_name": "cosine"
 }

onnx/model.onnx

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1680e5ce82aabe8e69d9ad6d76a854bbc31dc68ea6a69376b9f2a5e35fdb60f5
+size 1110092472

tokenizer.json

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f1cc44ad7faaeec47241864835473fd5403f2da94673f3f764a77ebcb0a803ec
-size 17083009
+oid sha256:883b037111086fd4dfebbbc9b7cee11e1517b5e0c0514879478661440f137085
+size 17082987

tokenizer_config.json

@@ -45,10 +45,18 @@
   "clean_up_tokenization_spaces": true,
   "cls_token": "<s>",
   "eos_token": "</s>",
+  "extra_special_tokens": {},
   "mask_token": "<mask>",
+  "max_length": 512,
   "model_max_length": 512,
+  "pad_to_multiple_of": null,
   "pad_token": "<pad>",
+  "pad_token_type_id": 0,
+  "padding_side": "right",
   "sep_token": "</s>",
+  "stride": 0,
   "tokenizer_class": "XLMRobertaTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
   "unk_token": "<unk>"
 }