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--- |
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library_name: onnx |
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tags: |
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- sentence-transformers |
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- sentence-similarity |
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- feature-extraction |
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- mpnet |
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- onnx |
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- inference4j |
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license: apache-2.0 |
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pipeline_tag: sentence-similarity |
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--- |
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# all-mpnet-base-v2 — ONNX |
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ONNX export of [all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2), the highest-quality sentence-transformers model based on MPNet. Maps sentences to a 768-dimensional dense vector space. |
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Mirrored for use with [inference4j](https://github.com/inference4j/inference4j), an inference-only AI library for Java. |
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## Original Source |
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- **Repository:** [sentence-transformers](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) |
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- **License:** apache-2.0 |
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## Usage with inference4j |
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```java |
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try (SentenceTransformer model = SentenceTransformer.fromPretrained("models/all-mpnet-base-v2")) { |
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float[] embedding = model.encode("Hello, world!"); |
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System.out.println("Dimension: " + embedding.length); // 768 |
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} |
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``` |
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## Model Details |
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| Property | Value | |
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|----------|-------| |
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| Architecture | MPNet-base (12 layers, 768 hidden) | |
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| Task | Sentence embeddings / semantic similarity | |
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| Output dimension | 768 | |
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| Max sequence length | 384 | |
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| Training data | 1B+ sentence pairs | |
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| Original framework | PyTorch (sentence-transformers) | |
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## License |
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This model is licensed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). Original model by [sentence-transformers](https://huggingface.co/sentence-transformers). |
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