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--- |
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language: |
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- zh |
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base_model: OpenSearch-AI/Ops-MoA-Yuan-embedding-1.0 |
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model-index: |
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- name: Ops-MoA-Yuan-embedding-1.0 |
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results: |
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- task: |
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type: Retrieval |
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dataset: |
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type: C-MTEB/CmedqaRetrieval |
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name: MTEB CmedqaRetrieval |
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config: default |
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split: dev |
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revision: cd540c506dae1cf9e9a59c3e06f42030d54e7301 |
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metrics: |
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- type: ndcg_at_10 |
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value: 51.461 |
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- task: |
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type: Retrieval |
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dataset: |
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type: C-MTEB/CovidRetrieval |
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name: MTEB CovidRetrieval |
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config: default |
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split: dev |
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revision: 1271c7809071a13532e05f25fb53511ffce77117 |
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metrics: |
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- type: ndcg_at_10 |
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value: 93.2 |
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- task: |
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type: Retrieval |
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dataset: |
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type: C-MTEB/DuRetrieval |
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name: MTEB DuRetrieval |
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config: default |
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split: dev |
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revision: a1a333e290fe30b10f3f56498e3a0d911a693ced |
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metrics: |
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- type: ndcg_at_10 |
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value: 89.84 |
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- task: |
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type: Retrieval |
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dataset: |
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type: C-MTEB/EcomRetrieval |
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name: MTEB EcomRetrieval |
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config: default |
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split: dev |
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revision: 687de13dc7294d6fd9be10c6945f9e8fec8166b9 |
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metrics: |
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- type: ndcg_at_10 |
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value: 71.084 |
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- task: |
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type: Retrieval |
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dataset: |
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type: C-MTEB/MMarcoRetrieval |
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name: MTEB MMarcoRetrieval |
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config: default |
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split: dev |
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revision: 539bbde593d947e2a124ba72651aafc09eb33fc2 |
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metrics: |
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- type: ndcg_at_10 |
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value: 82.43 |
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- task: |
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type: Retrieval |
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dataset: |
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type: C-MTEB/MedicalRetrieval |
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name: MTEB MedicalRetrieval |
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config: default |
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split: dev |
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revision: 2039188fb5800a9803ba5048df7b76e6fb151fc6 |
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metrics: |
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- type: ndcg_at_10 |
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value: 74.848 |
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- task: |
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type: Retrieval |
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dataset: |
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type: C-MTEB/T2Retrieval |
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name: MTEB T2Retrieval |
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config: default |
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split: dev |
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revision: 8731a845f1bf500a4f111cf1070785c793d10e64 |
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metrics: |
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- type: ndcg_at_10 |
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value: 85.784 |
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- task: |
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type: Retrieval |
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dataset: |
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type: C-MTEB/VideoRetrieval |
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name: MTEB VideoRetrieval |
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config: default |
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split: dev |
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revision: 58c2597a5943a2ba48f4668c3b90d796283c5639 |
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metrics: |
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- type: ndcg_at_10 |
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value: 79.513 |
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pipeline_tag: feature-extraction |
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tags: |
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- mteb |
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- sentence-transformers |
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--- |
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```python |
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from sentence_transformers import SentenceTransformer |
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model = SentenceTransformer("OpenSearch-AI/Ops-MoA-Yuan-embedding-1.0") |
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model.encode(['text']) |
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``` |
