Add openvino/ from beclab/embeddinggemma-300m-ov

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
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openvino/.gitattributes

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openvino/2_Dense/config.json

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+{
+    "in_features": 768,
+    "out_features": 3072,
+    "bias": false,
+    "activation_function": "torch.nn.modules.linear.Identity"
+}

openvino/2_Dense/model.safetensors

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openvino/3_Dense/config.json

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+    "in_features": 3072,
+    "out_features": 768,
+    "bias": false,
+    "activation_function": "torch.nn.modules.linear.Identity"
+}

openvino/3_Dense/model.safetensors

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openvino/README.md

@@ -0,0 +1,41 @@
+---
+language:
+- en
+- multilingual
+license: gemma
+base_model: google/embeddinggemma-300m
+tags:
+- openvino
+- feature-extraction
+- sentence-similarity
+- sentence-transformers
+- text-embeddings-inference
+library_name: sentence-transformers
+pipeline_tag: feature-extraction
+---
+
+# EmbeddingGemma-300M OpenVINO FP32
+
+OpenVINO IR (FP32) export of [google/embeddinggemma-300m](https://huggingface.co/google/embeddinggemma-300m),
+packaged for [IREmbeddingServer](https://github.com/) inference (`MODEL_ID=embeddinggemma-300m-ov`).
+
+## Layout
+
+| Path | Description |
+|------|-------------|
+| `openvino_model.xml` / `openvino_model.bin` | Gemma3 backbone IR (~1.2GB FP32) |
+| `2_Dense/` / `3_Dense/` | Sentence Transformers Dense layers (post-OV matmul) |
+| `tokenizer.json` | Tokenizer |
+| `modules.json` | ST module metadata |
+
+## IREmbeddingServer
+
+```bash
+export EMBED_MODEL_DIR="./embeddinggemma-300m-ov"
+export MODEL_ID=embeddinggemma-300m-ov
+export EMBED_DEVICE=cpu   # or igpu / npu
+```
+
+## License
+
+Derived from Google's EmbeddingGemma (Gemma license). See [google/embeddinggemma-300m](https://huggingface.co/google/embeddinggemma-300m).

openvino/added_tokens.json

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+{
+  "<image_soft_token>": 262144
+}

openvino/config.json

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+{
+  "_sliding_window_pattern": 6,
+  "architectures": [
+    "Gemma3TextModel"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "attn_logit_softcapping": null,
+  "bos_token_id": 2,
+  "dtype": "float32",
+  "eos_token_id": 1,
+  "final_logit_softcapping": null,
+  "head_dim": 256,
+  "hidden_activation": "gelu_pytorch_tanh",
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 1152,
+  "layer_types": [
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
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+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 2048,
+  "model_type": "gemma3_text",
+  "num_attention_heads": 3,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 1,
+  "pad_token_id": 0,
+  "query_pre_attn_scalar": 256,
+  "rms_norm_eps": 1e-06,
+  "rope_local_base_freq": 10000.0,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": 512,
+  "transformers_version": "4.57.0.dev0",
+  "use_bidirectional_attention": true,
+  "use_cache": true,
+  "vocab_size": 262144
+}

openvino/config_sentence_transformers.json

@@ -0,0 +1,26 @@
+{
+  "model_type": "SentenceTransformer",
+  "__version__": {
+    "sentence_transformers": "5.1.0",
+    "transformers": "4.57.0.dev0",
+    "pytorch": "2.8.0+cu128"
+  },
+  "prompts": {
+    "query": "task: search result | query: ",
+    "document": "title: none | text: ",
+    "BitextMining": "task: search result | query: ",
+    "Clustering": "task: clustering | query: ",
+    "Classification": "task: classification | query: ",
+    "InstructionRetrieval": "task: code retrieval | query: ",
+    "MultilabelClassification": "task: classification | query: ",
+    "PairClassification": "task: sentence similarity | query: ",
+    "Reranking": "task: search result | query: ",
+    "Retrieval": "task: search result | query: ",
+    "Retrieval-query": "task: search result | query: ",
+    "Retrieval-document": "title: none | text: ",
+    "STS": "task: sentence similarity | query: ",
+    "Summarization": "task: summarization | query: "
+  },
+  "default_prompt_name": null,
+  "similarity_fn_name": "cosine"
+}

openvino/modules.json

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+[
+  {
+    "idx": 0,
+    "name": "0",
+    "path": "",
+    "type": "sentence_transformers.models.Transformer"
+  },
+  {
+    "idx": 1,
+    "name": "1",
+    "path": "1_Pooling",
+    "type": "sentence_transformers.models.Pooling"
+  },
+  {
+    "idx": 2,
+    "name": "2",
+    "path": "2_Dense",
+    "type": "sentence_transformers.models.Dense"
+  },
+  {
+    "idx": 3,
+    "name": "3",
+    "path": "3_Dense",
+    "type": "sentence_transformers.models.Dense"
+  },
+  {
+    "idx": 4,
+    "name": "4",
+    "path": "4_Normalize",
+    "type": "sentence_transformers.models.Normalize"
+  }
+]

openvino/openvino_model.bin

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openvino/sentence_bert_config.json

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+{
+    "max_seq_length": 2048,
+    "do_lower_case": false
+}

openvino/special_tokens_map.json

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+{
+  "boi_token": "<start_of_image>",
+  "bos_token": {
+    "content": "<bos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eoi_token": "<end_of_image>",
+  "eos_token": {
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
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+    "single_word": false
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

openvino/tokenizer.json

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openvino/tokenizer.model

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