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bge-base-en-v1.5
inference4j/bge-base-en-v1.5
bge-base-en-v1.5 is a sentence similarity model from inference4j. Use it when you need a score for how close two texts are. It is set up for onnx. The card lists the license as mit.
ONNX export of 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.
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Public
Updated Mar 2, 2026
Repo size
436 MB
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At a glance
- Task
- Sentence Similarity
- Library
- onnx
- License
- mit
- Access
- Public
- Created
- Mar 2, 2026
- Updated
- Mar 2, 2026
- SHA
- 79b7fc1c
Model card
From the Hugging Face model README
BGE Base EN v1.5 — ONNX
ONNX export of 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, an inference-only AI library for Java.
Original Source
- Repository: BAAI (ONNX by Xenova)
- License: mit
Usage with inference4j
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. Original model by BAAI, ONNX export by Xenova.
- Task
- Sentence Similarity
- Library
- onnx
- License
- mit
- Created
- Mar 2, 2026
- Updated
- Mar 2, 2026