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| license: mit | |
| base_model: jhu-clsp/ettin-encoder-1b | |
| library_name: onnx | |
| pipeline_tag: feature-extraction | |
| tags: [code-search, retrieval, onnx, anvesa] | |
| # anvesa-code-1b | |
| A code-search encoder for [anvesa](https://github.com/nimishph/anvesa): Ettin-encoder-1b (jhu-clsp, MIT) fine-tuned | |
| on 105 MIT-licensed repositories. ONNX, fp32: `model.onnx` with its weights in `model.onnx_data`, and | |
| `tokenizer.json`. Mean pooling over real tokens, L2-normalised, 512 tokens, no prefix. It embeds anvesa's symbol | |
| cards without their WQL path line. | |
| `ranker-noword.json` is the XGBoost ranker fit on this encoder's scores for anvesa's `experimental.learnedRanker` | |
| (20 features, no word overlap). | |
| | | corpus test (1,710 generated queries, 57 repos, 13 languages) | bench (241 hand-written queries, 8 repos) | | |
| |---|---|---| | |
| | first stage, hub penalty 0.3 | 0.352 | 0.685 | | |
| | with the ranker | 0.370 | 0.699 | | |
| CPU: 373 ms a card (ONNX Runtime, 12 threads). For comparison, all-MiniLM-L6-v2 scores 0.293 and 0.547 without a | |
| ranker. | |
| ```bash | |
| anvesa model install anvesa-code-1b --download | |
| ``` | |