multilingual, qa, paraphrase (onnx)

.gitattributes

@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 MPNet.[[:space:]]Masked[[:space:]]and[[:space:]]Permuted[[:space:]]Pre-training[[:space:]]for[[:space:]]Language[[:space:]]Understanding.pdf filter=lfs diff=lfs merge=lfs -text
+sbert-paraphrase-multilingual-mpnet-base-v2-onnx/tokenizer.json filter=lfs diff=lfs merge=lfs -text

multi-qa-mpnet-base-cos-v1-onnx/.gitattributes

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+*.npy filter=lfs diff=lfs merge=lfs -text
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multi-qa-mpnet-base-cos-v1-onnx/README.md

@@ -0,0 +1,61 @@
+---
+library_name: light-embed
+pipeline_tag: sentence-similarity
+tags:
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+
+---
+
+# onnx-models/multi-qa-mpnet-base-cos-v1-onnx
+
+This is the ONNX-ported version of the [sentence-transformers/multi-qa-mpnet-base-cos-v1](https://huggingface.co/sentence-transformers/multi-qa-mpnet-base-cos-v1) for generating text embeddings.
+
+## Model details
+- Embedding dimension: 768
+- Max sequence length: 512
+- File size on disk:  0.41 GB
+- Modules incorporated in the onnx: Transformer, Pooling, Normalize
+
+<!--- Describe your model here -->
+
+## Usage
+
+Using this model becomes easy when you have [light-embed](https://pypi.org/project/light-embed/) installed:
+
+```
+pip install -U light-embed
+```
+
+Then you can use the model by specifying the *original model name* like this:
+
+```python
+from light_embed import TextEmbedding
+sentences = [
+	"This is an example sentence",
+	"Each sentence is converted"
+]
+
+model = TextEmbedding('sentence-transformers/multi-qa-mpnet-base-cos-v1')
+embeddings = model.encode(sentences)
+print(embeddings)
+```
+
+or by specifying the *onnx model name* like this:
+
+```python
+from light_embed import TextEmbedding
+sentences = [
+	"This is an example sentence",
+	"Each sentence is converted"
+]
+
+model = TextEmbedding('onnx-models/multi-qa-mpnet-base-cos-v1-onnx')
+embeddings = model.encode(sentences)
+print(embeddings)
+```
+
+## Citing & Authors
+
+Binh Nguyen / binhcode25@gmail.com

multi-qa-mpnet-base-cos-v1-onnx/config.json

@@ -0,0 +1,23 @@
+{
+  "_name_or_path": "sentence-transformers/multi-qa-mpnet-base-cos-v1",
+  "architectures": [
+    "MPNetForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "mpnet",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "relative_attention_num_buckets": 32,
+  "transformers_version": "4.8.2",
+  "vocab_size": 30527
+}

multi-qa-mpnet-base-cos-v1-onnx/model.onnx

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multi-qa-mpnet-base-cos-v1-onnx/source.txt

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+https://huggingface.co/onnx-models/multi-qa-mpnet-base-cos-v1-onnx

multi-qa-mpnet-base-cos-v1-onnx/special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "cls_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

multi-qa-mpnet-base-cos-v1-onnx/tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "104": {
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+      "special": true
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+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "do_lower_case": true,
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "max_length": 250,
+  "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,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "MPNetTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}

multi-qa-mpnet-base-dot-v1-onnx/.gitattributes

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multi-qa-mpnet-base-dot-v1-onnx/README.md

@@ -0,0 +1,61 @@
+---
+library_name: light-embed
+pipeline_tag: sentence-similarity
+tags:
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+
+---
+
+# onnx-models/multi-qa-mpnet-base-dot-v1-onnx
+
+This is the ONNX-ported version of the [sentence-transformers/multi-qa-mpnet-base-dot-v1](https://huggingface.co/sentence-transformers/multi-qa-mpnet-base-dot-v1) for generating text embeddings.
+
+## Model details
+- Embedding dimension: 768
+- Max sequence length: 512
+- File size on disk:  0.41 GB
+- Modules incorporated in the onnx: Transformer, Pooling
+
+<!--- Describe your model here -->
+
+## Usage
+
+Using this model becomes easy when you have [light-embed](https://pypi.org/project/light-embed/) installed:
+
+```
+pip install -U light-embed
+```
+
+Then you can use the model by specifying the *original model name* like this:
+
+```python
+from light_embed import TextEmbedding
+sentences = [
+	"This is an example sentence",
+	"Each sentence is converted"
+]
+
+model = TextEmbedding('sentence-transformers/multi-qa-mpnet-base-dot-v1')
+embeddings = model.encode(sentences)
+print(embeddings)
+```
+
+or by specifying the *onnx model name* like this:
+
+```python
+from light_embed import TextEmbedding
+sentences = [
+	"This is an example sentence",
+	"Each sentence is converted"
+]
+
+model = TextEmbedding('onnx-models/multi-qa-mpnet-base-dot-v1-onnx')
+embeddings = model.encode(sentences)
+print(embeddings)
+```
+
+## Citing & Authors
+
+Binh Nguyen / binhcode25@gmail.com

multi-qa-mpnet-base-dot-v1-onnx/config.json

@@ -0,0 +1,23 @@
+{
+  "_name_or_path": "sentence-transformers/multi-qa-mpnet-base-dot-v1",
+  "architectures": [
+    "MPNetForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "mpnet",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "relative_attention_num_buckets": 32,
+  "transformers_version": "4.8.2",
+  "vocab_size": 30527
+}

multi-qa-mpnet-base-dot-v1-onnx/model.onnx

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multi-qa-mpnet-base-dot-v1-onnx/source.txt

@@ -0,0 +1 @@
+https://huggingface.co/onnx-models/multi-qa-mpnet-base-dot-v1-onnx

multi-qa-mpnet-base-dot-v1-onnx/special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "mask_token": {
+    "content": "<mask>",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "sep_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

multi-qa-mpnet-base-dot-v1-onnx/tokenizer_config.json

@@ -0,0 +1,72 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "3": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "104": {
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+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "do_lower_case": true,
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "max_length": 250,
+  "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,
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "MPNetTokenizer",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "[UNK]"
+}

paraphrase-mpnet-base-v2-onnx/.gitattributes

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+*.onnx filter=lfs diff=lfs merge=lfs -text
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+*.pth filter=lfs diff=lfs merge=lfs -text
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+*.safetensors filter=lfs diff=lfs merge=lfs -text
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+*.tar.* filter=lfs diff=lfs merge=lfs -text
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paraphrase-mpnet-base-v2-onnx/README.md

@@ -0,0 +1,61 @@
+---
+library_name: light-embed
+pipeline_tag: sentence-similarity
+tags:
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+
+---
+
+# onnx-models/paraphrase-mpnet-base-v2-onnx
+
+This is the ONNX-ported version of the [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2) for generating text embeddings.
+
+## Model details
+- Embedding dimension: 768
+- Max sequence length: 512
+- File size on disk:  0.41 GB
+- Modules incorporated in the onnx: Transformer, Pooling
+
+<!--- Describe your model here -->
+
+## Usage
+
+Using this model becomes easy when you have [light-embed](https://pypi.org/project/light-embed/) installed:
+
+```
+pip install -U light-embed
+```
+
+Then you can use the model by specifying the *original model name* like this:
+
+```python
+from light_embed import TextEmbedding
+sentences = [
+	"This is an example sentence",
+	"Each sentence is converted"
+]
+
+model = TextEmbedding('sentence-transformers/paraphrase-mpnet-base-v2')
+embeddings = model.encode(sentences)
+print(embeddings)
+```
+
+or by specifying the *onnx model name* like this:
+
+```python
+from light_embed import TextEmbedding
+sentences = [
+	"This is an example sentence",
+	"Each sentence is converted"
+]
+
+model = TextEmbedding('onnx-models/paraphrase-mpnet-base-v2-onnx')
+embeddings = model.encode(sentences)
+print(embeddings)
+```
+
+## Citing & Authors
+
+Binh Nguyen / binhcode25@gmail.com

paraphrase-mpnet-base-v2-onnx/config.json

@@ -0,0 +1,23 @@
+{
+  "_name_or_path": "sentence-transformers/paraphrase-mpnet-base-v2",
+  "architectures": [
+    "MPNetModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "mpnet",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "relative_attention_num_buckets": 32,
+  "transformers_version": "4.7.0",
+  "vocab_size": 30527
+}

paraphrase-mpnet-base-v2-onnx/model.onnx

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paraphrase-multilingual-mpnet-base-v2-onnx/package.json

@@ -0,0 +1,12 @@
+{
+  "name": "embedding",
+  "version": "0.1.0",
+  "private": false,
+  "type": "module",
+  "main": "index.js",
+  "scripts": {
+  },
+  "dependencies": {
+    "@xenova/transformers": "^2.8.0"
+  }
+}

paraphrase-multilingual-mpnet-base-v2-onnx/sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+  "max_seq_length": 128,
+  "do_lower_case": false
+}

paraphrase-multilingual-mpnet-base-v2-onnx/source.txt

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+https://huggingface.co/tzmtwtr/paraphrase-multilingual-mpnet-base-v2-onnx

paraphrase-multilingual-mpnet-base-v2-onnx/special_tokens_map.json

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+{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": false}}

paraphrase-multilingual-mpnet-base-v2-onnx/tokenizer_config.json

@@ -0,0 +1,20 @@
+{
+    "bos_token": "<s>",
+    "eos_token": "</s>",
+    "sep_token": "</s>",
+    "cls_token": "<s>",
+    "unk_token": "<unk>",
+    "pad_token": "<pad>",
+    "mask_token": {
+        "content": "<mask>",
+        "single_word": false,
+        "lstrip": true,
+        "rstrip": false,
+        "normalized": true,
+        "__type": "AddedToken"
+    },
+    "model_max_length": 512,
+    "special_tokens_map_file": null,
+    "name_or_path": "old_models/paraphrase-multilingual-mpnet-base-v2/0_Transformer",
+    "tokenizer_class": "PreTrainedTokenizerFast"
+}

sbert-paraphrase-multilingual-mpnet-base-v2-onnx/.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
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+*.bz2 filter=lfs diff=lfs merge=lfs -text
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+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
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+tokenizer.json filter=lfs diff=lfs merge=lfs -text

sbert-paraphrase-multilingual-mpnet-base-v2-onnx/1_Pooling/config.json

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+{
+  "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
+}

sbert-paraphrase-multilingual-mpnet-base-v2-onnx/README.md

@@ -0,0 +1,63 @@
+---
+library_name: light-embed
+pipeline_tag: sentence-similarity
+tags:
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+
+---
+
+# LightEmbed/sbert-paraphrase-multilingual-mpnet-base-v2-onnx
+
+This is the ONNX version of the Sentence Transformers model sentence-transformers/paraphrase-multilingual-mpnet-base-v2 for sentence embedding, optimized for speed and lightweight performance. By utilizing onnxruntime and tokenizers instead of heavier libraries like sentence-transformers and transformers, this version ensures a smaller library size and faster execution. Below are the details of the model:
+- Base model: sentence-transformers/paraphrase-multilingual-mpnet-base-v2
+- Embedding dimension: 768
+- Max sequence length: 128
+- File size on disk:  1.03 GB
+- Pooling incorporated: Yes
+
+This ONNX model consists all components in the original sentence transformer model:
+Transformer, Pooling
+
+<!--- Describe your model here -->
+
+## Usage (LightEmbed)
+
+Using this model becomes easy when you have [LightEmbed](https://pypi.org/project/light-embed/) installed:
+
+```
+pip install -U light-embed
+```
+
+Then you can use the model using the original model name like this:
+
+```python
+from light_embed import TextEmbedding
+sentences = [
+	"This is an example sentence",
+	"Each sentence is converted"
+]
+
+model = TextEmbedding('sentence-transformers/paraphrase-multilingual-mpnet-base-v2')
+embeddings = model.encode(sentences)
+print(embeddings)
+```
+
+Then you can use the model using onnx model name like this:
+
+```python
+from light_embed import TextEmbedding
+sentences = [
+	"This is an example sentence",
+	"Each sentence is converted"
+]
+
+model = TextEmbedding('LightEmbed/sbert-paraphrase-multilingual-mpnet-base-v2-onnx')
+embeddings = model.encode(sentences)
+print(embeddings)
+```
+
+## Citing & Authors
+
+Binh Nguyen / binhcode25@gmail.com

sbert-paraphrase-multilingual-mpnet-base-v2-onnx/config.json

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+{
+  "_name_or_path": "sentence-transformers/paraphrase-multilingual-mpnet-base-v2",
+  "architectures": [
+    "XLMRobertaModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "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",
+  "transformers_version": "4.7.0",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

sbert-paraphrase-multilingual-mpnet-base-v2-onnx/config_sentence_transformers.json

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+{
+  "__version__": {
+    "sentence_transformers": "2.0.0",
+    "transformers": "4.7.0",
+    "pytorch": "1.9.0+cu102"
+  }
+}

sbert-paraphrase-multilingual-mpnet-base-v2-onnx/model.onnx

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+size 1110169968

sbert-paraphrase-multilingual-mpnet-base-v2-onnx/model_description.json

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+{
+  "model_name": "LightEmbed/sbert-paraphrase-multilingual-mpnet-base-v2-onnx",
+  "base_model": "sentence-transformers/paraphrase-multilingual-mpnet-base-v2",
+  "model_file": "model.onnx",
+  "embedding_dim": 768,
+  "max_seq_length": 128,
+  "model_file_size (GB)": 1.03
+}

sbert-paraphrase-multilingual-mpnet-base-v2-onnx/model_info.json

@@ -0,0 +1,6 @@
+{
+   "description": "Sentence Transformer model, paraphrase-multilingual-mpnet-base-v2",
+   "base_model": "sentence-transformers/paraphrase-multilingual-mpnet-base-v2",
+   "dim": 768,
+   "max_seq_length": 128
+}