Upload bge-base-en-v1.5 ONNX model

README.md

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+---
+library_name: onnx
+tags:
+  - bge
+  - sentence-transformers
+  - sentence-similarity
+  - feature-extraction
+  - onnx
+  - inference4j
+license: mit
+pipeline_tag: sentence-similarity
+---
+
+# BGE Base EN v1.5 — ONNX
+
+ONNX export of [BAAI/bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5), a high-quality English embedding model. Maps sentences to 768-dimensional dense vectors using CLS pooling with L2 normalization.
+
+Mirrored for use with [inference4j](https://github.com/inference4j/inference4j), an inference-only AI library for Java.
+
+## Original Source
+
+- **Repository:** [BAAI (ONNX by Xenova)](https://huggingface.co/BAAI/bge-base-en-v1.5)
+- **License:** mit
+
+## Usage with inference4j
+
+```java
+try (SentenceTransformerEmbedder model = SentenceTransformerEmbedder.builder()
+        .modelId("inference4j/bge-base-en-v1.5")
+        .poolingStrategy(PoolingStrategy.CLS)
+        .normalize()
+        .build()) {
+    float[] embedding = model.encode("Hello, world!");
+    System.out.println("Dimension: " + embedding.length); // 768
+}
+```
+
+## Model Details
+
+| Property | Value |
+|----------|-------|
+| Architecture | BERT Base (12 layers, 768 hidden) |
+| Task | Sentence embeddings / semantic similarity |
+| Output dimension | 768 |
+| Pooling | CLS |
+| Normalization | L2 |
+| MTEB average | 63.55 |
+| Max sequence length | 512 |
+| Original framework | PyTorch (HuggingFace Transformers) |
+
+## License
+
+This model is licensed under the [MIT License](https://opensource.org/licenses/MIT). Original model by [BAAI](https://huggingface.co/BAAI/bge-base-en-v1.5), ONNX export by [Xenova](https://huggingface.co/Xenova).

model.onnx

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