| --- |
| license: mit |
| base_model: jhu-clsp/ettin-encoder-400m |
| library_name: onnx |
| pipeline_tag: feature-extraction |
| tags: [code-search, retrieval, onnx, anvesa] |
| --- |
| |
| # anvesa-code-400m |
|
|
| A code-search encoder for [anvesa](https://github.com/nimishph/anvesa): Ettin-encoder-400m (jhu-clsp, MIT) fine-tuned |
| on 105 MIT-licensed repositories, learning from the 1B fine-tune as a teacher. 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 | 0.349 | 0.684 | |
| | with the ranker | 0.369 | 0.682 | |
|
|
| CPU: 98 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-400m --download |
| ``` |
|
|
