| --- |
| tags: |
| - mteb |
| - sentence-transfomres |
| - transformers |
| - llama-cpp |
| - gguf-my-repo |
| license: mit |
| language: |
| - en |
| base_model: BAAI/bge-large-en |
| model-index: |
| - name: bge-large-en |
| results: |
| - task: |
| type: Classification |
| dataset: |
| name: MTEB AmazonCounterfactualClassification (en) |
| type: mteb/amazon_counterfactual |
| config: en |
| split: test |
| revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
| metrics: |
| - type: accuracy |
| value: 76.94029850746269 |
| - type: ap |
| value: 40.00228964744091 |
| - type: f1 |
| value: 70.86088267934595 |
| - task: |
| type: Classification |
| dataset: |
| name: MTEB AmazonPolarityClassification |
| type: mteb/amazon_polarity |
| config: default |
| split: test |
| revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
| metrics: |
| - type: accuracy |
| value: 91.93745 |
| - type: ap |
| value: 88.24758534667426 |
| - type: f1 |
| value: 91.91033034217591 |
| - task: |
| type: Classification |
| dataset: |
| name: MTEB AmazonReviewsClassification (en) |
| type: mteb/amazon_reviews_multi |
| config: en |
| split: test |
| revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| metrics: |
| - type: accuracy |
| value: 46.158 |
| - type: f1 |
| value: 45.78935185074774 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB ArguAna |
| type: arguana |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 39.972 |
| - type: map_at_10 |
| value: 54.874 |
| - type: map_at_100 |
| value: 55.53399999999999 |
| - type: map_at_1000 |
| value: 55.539 |
| - type: map_at_3 |
| value: 51.031000000000006 |
| - type: map_at_5 |
| value: 53.342999999999996 |
| - type: mrr_at_1 |
| value: 40.541 |
| - type: mrr_at_10 |
| value: 55.096000000000004 |
| - type: mrr_at_100 |
| value: 55.75599999999999 |
| - type: mrr_at_1000 |
| value: 55.761 |
| - type: mrr_at_3 |
| value: 51.221000000000004 |
| - type: mrr_at_5 |
| value: 53.568000000000005 |
| - type: ndcg_at_1 |
| value: 39.972 |
| - type: ndcg_at_10 |
| value: 62.456999999999994 |
| - type: ndcg_at_100 |
| value: 65.262 |
| - type: ndcg_at_1000 |
| value: 65.389 |
| - type: ndcg_at_3 |
| value: 54.673 |
| - type: ndcg_at_5 |
| value: 58.80499999999999 |
| - type: precision_at_1 |
| value: 39.972 |
| - type: precision_at_10 |
| value: 8.634 |
| - type: precision_at_100 |
| value: 0.9860000000000001 |
| - type: precision_at_1000 |
| value: 0.1 |
| - type: precision_at_3 |
| value: 21.740000000000002 |
| - type: precision_at_5 |
| value: 15.036 |
| - type: recall_at_1 |
| value: 39.972 |
| - type: recall_at_10 |
| value: 86.344 |
| - type: recall_at_100 |
| value: 98.578 |
| - type: recall_at_1000 |
| value: 99.57300000000001 |
| - type: recall_at_3 |
| value: 65.22 |
| - type: recall_at_5 |
| value: 75.178 |
| - task: |
| type: Clustering |
| dataset: |
| name: MTEB ArxivClusteringP2P |
| type: mteb/arxiv-clustering-p2p |
| config: default |
| split: test |
| revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| metrics: |
| - type: v_measure |
| value: 48.94652870403906 |
| - task: |
| type: Clustering |
| dataset: |
| name: MTEB ArxivClusteringS2S |
| type: mteb/arxiv-clustering-s2s |
| config: default |
| split: test |
| revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
| metrics: |
| - type: v_measure |
| value: 43.17257160340209 |
| - task: |
| type: Reranking |
| dataset: |
| name: MTEB AskUbuntuDupQuestions |
| type: mteb/askubuntudupquestions-reranking |
| config: default |
| split: test |
| revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
| metrics: |
| - type: map |
| value: 63.97867370559182 |
| - type: mrr |
| value: 77.00820032537484 |
| - task: |
| type: STS |
| dataset: |
| name: MTEB BIOSSES |
| type: mteb/biosses-sts |
| config: default |
| split: test |
| revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
| metrics: |
| - type: cos_sim_pearson |
| value: 80.00986015960616 |
| - type: cos_sim_spearman |
| value: 80.36387933827882 |
| - type: euclidean_pearson |
| value: 80.32305287257296 |
| - type: euclidean_spearman |
| value: 82.0524720308763 |
| - type: manhattan_pearson |
| value: 80.19847473906454 |
| - type: manhattan_spearman |
| value: 81.87957652506985 |
| - task: |
| type: Classification |
| dataset: |
| name: MTEB Banking77Classification |
| type: mteb/banking77 |
| config: default |
| split: test |
| revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| metrics: |
| - type: accuracy |
| value: 88.00000000000001 |
| - type: f1 |
| value: 87.99039027511853 |
| - task: |
| type: Clustering |
| dataset: |
| name: MTEB BiorxivClusteringP2P |
| type: mteb/biorxiv-clustering-p2p |
| config: default |
| split: test |
| revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| metrics: |
| - type: v_measure |
| value: 41.36932844640705 |
| - task: |
| type: Clustering |
| dataset: |
| name: MTEB BiorxivClusteringS2S |
| type: mteb/biorxiv-clustering-s2s |
| config: default |
| split: test |
| revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
| metrics: |
| - type: v_measure |
| value: 38.34983239611985 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB CQADupstackAndroidRetrieval |
| type: BeIR/cqadupstack |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 32.257999999999996 |
| - type: map_at_10 |
| value: 42.937 |
| - type: map_at_100 |
| value: 44.406 |
| - type: map_at_1000 |
| value: 44.536 |
| - type: map_at_3 |
| value: 39.22 |
| - type: map_at_5 |
| value: 41.458 |
| - type: mrr_at_1 |
| value: 38.769999999999996 |
| - type: mrr_at_10 |
| value: 48.701 |
| - type: mrr_at_100 |
| value: 49.431000000000004 |
| - type: mrr_at_1000 |
| value: 49.476 |
| - type: mrr_at_3 |
| value: 45.875 |
| - type: mrr_at_5 |
| value: 47.67 |
| - type: ndcg_at_1 |
| value: 38.769999999999996 |
| - type: ndcg_at_10 |
| value: 49.35 |
| - type: ndcg_at_100 |
| value: 54.618 |
| - type: ndcg_at_1000 |
| value: 56.655 |
| - type: ndcg_at_3 |
| value: 43.826 |
| - type: ndcg_at_5 |
| value: 46.72 |
| - type: precision_at_1 |
| value: 38.769999999999996 |
| - type: precision_at_10 |
| value: 9.328 |
| - type: precision_at_100 |
| value: 1.484 |
| - type: precision_at_1000 |
| value: 0.196 |
| - type: precision_at_3 |
| value: 20.649 |
| - type: precision_at_5 |
| value: 15.25 |
| - type: recall_at_1 |
| value: 32.257999999999996 |
| - type: recall_at_10 |
| value: 61.849 |
| - type: recall_at_100 |
| value: 83.70400000000001 |
| - type: recall_at_1000 |
| value: 96.344 |
| - type: recall_at_3 |
| value: 46.037 |
| - type: recall_at_5 |
| value: 53.724000000000004 |
| - type: map_at_1 |
| value: 32.979 |
| - type: map_at_10 |
| value: 43.376999999999995 |
| - type: map_at_100 |
| value: 44.667 |
| - type: map_at_1000 |
| value: 44.794 |
| - type: map_at_3 |
| value: 40.461999999999996 |
| - type: map_at_5 |
| value: 42.138 |
| - type: mrr_at_1 |
| value: 41.146 |
| - type: mrr_at_10 |
| value: 49.575 |
| - type: mrr_at_100 |
| value: 50.187000000000005 |
| - type: mrr_at_1000 |
| value: 50.231 |
| - type: mrr_at_3 |
| value: 47.601 |
| - type: mrr_at_5 |
| value: 48.786 |
| - type: ndcg_at_1 |
| value: 41.146 |
| - type: ndcg_at_10 |
| value: 48.957 |
| - type: ndcg_at_100 |
| value: 53.296 |
| - type: ndcg_at_1000 |
| value: 55.254000000000005 |
| - type: ndcg_at_3 |
| value: 45.235 |
| - type: ndcg_at_5 |
| value: 47.014 |
| - type: precision_at_1 |
| value: 41.146 |
| - type: precision_at_10 |
| value: 9.107999999999999 |
| - type: precision_at_100 |
| value: 1.481 |
| - type: precision_at_1000 |
| value: 0.193 |
| - type: precision_at_3 |
| value: 21.783 |
| - type: precision_at_5 |
| value: 15.274 |
| - type: recall_at_1 |
| value: 32.979 |
| - type: recall_at_10 |
| value: 58.167 |
| - type: recall_at_100 |
| value: 76.374 |
| - type: recall_at_1000 |
| value: 88.836 |
| - type: recall_at_3 |
| value: 46.838 |
| - type: recall_at_5 |
| value: 52.006 |
| - type: map_at_1 |
| value: 40.326 |
| - type: map_at_10 |
| value: 53.468 |
| - type: map_at_100 |
| value: 54.454 |
| - type: map_at_1000 |
| value: 54.508 |
| - type: map_at_3 |
| value: 50.12799999999999 |
| - type: map_at_5 |
| value: 51.991 |
| - type: mrr_at_1 |
| value: 46.394999999999996 |
| - type: mrr_at_10 |
| value: 57.016999999999996 |
| - type: mrr_at_100 |
| value: 57.67099999999999 |
| - type: mrr_at_1000 |
| value: 57.699999999999996 |
| - type: mrr_at_3 |
| value: 54.65 |
| - type: mrr_at_5 |
| value: 56.101 |
| - type: ndcg_at_1 |
| value: 46.394999999999996 |
| - type: ndcg_at_10 |
| value: 59.507 |
| - type: ndcg_at_100 |
| value: 63.31099999999999 |
| - type: ndcg_at_1000 |
| value: 64.388 |
| - type: ndcg_at_3 |
| value: 54.04600000000001 |
| - type: ndcg_at_5 |
| value: 56.723 |
| - type: precision_at_1 |
| value: 46.394999999999996 |
| - type: precision_at_10 |
| value: 9.567 |
| - type: precision_at_100 |
| value: 1.234 |
| - type: precision_at_1000 |
| value: 0.13699999999999998 |
| - type: precision_at_3 |
| value: 24.117 |
| - type: precision_at_5 |
| value: 16.426 |
| - type: recall_at_1 |
| value: 40.326 |
| - type: recall_at_10 |
| value: 73.763 |
| - type: recall_at_100 |
| value: 89.927 |
| - type: recall_at_1000 |
| value: 97.509 |
| - type: recall_at_3 |
| value: 59.34 |
| - type: recall_at_5 |
| value: 65.915 |
| - type: map_at_1 |
| value: 26.661 |
| - type: map_at_10 |
| value: 35.522 |
| - type: map_at_100 |
| value: 36.619 |
| - type: map_at_1000 |
| value: 36.693999999999996 |
| - type: map_at_3 |
| value: 33.154 |
| - type: map_at_5 |
| value: 34.353 |
| - type: mrr_at_1 |
| value: 28.362 |
| - type: mrr_at_10 |
| value: 37.403999999999996 |
| - type: mrr_at_100 |
| value: 38.374 |
| - type: mrr_at_1000 |
| value: 38.428000000000004 |
| - type: mrr_at_3 |
| value: 35.235 |
| - type: mrr_at_5 |
| value: 36.269 |
| - type: ndcg_at_1 |
| value: 28.362 |
| - type: ndcg_at_10 |
| value: 40.431 |
| - type: ndcg_at_100 |
| value: 45.745999999999995 |
| - type: ndcg_at_1000 |
| value: 47.493 |
| - type: ndcg_at_3 |
| value: 35.733 |
| - type: ndcg_at_5 |
| value: 37.722 |
| - type: precision_at_1 |
| value: 28.362 |
| - type: precision_at_10 |
| value: 6.101999999999999 |
| - type: precision_at_100 |
| value: 0.922 |
| - type: precision_at_1000 |
| value: 0.11100000000000002 |
| - type: precision_at_3 |
| value: 15.140999999999998 |
| - type: precision_at_5 |
| value: 10.305 |
| - type: recall_at_1 |
| value: 26.661 |
| - type: recall_at_10 |
| value: 53.675 |
| - type: recall_at_100 |
| value: 77.891 |
| - type: recall_at_1000 |
| value: 90.72 |
| - type: recall_at_3 |
| value: 40.751 |
| - type: recall_at_5 |
| value: 45.517 |
| - type: map_at_1 |
| value: 18.886 |
| - type: map_at_10 |
| value: 27.288 |
| - type: map_at_100 |
| value: 28.327999999999996 |
| - type: map_at_1000 |
| value: 28.438999999999997 |
| - type: map_at_3 |
| value: 24.453 |
| - type: map_at_5 |
| value: 25.959 |
| - type: mrr_at_1 |
| value: 23.134 |
| - type: mrr_at_10 |
| value: 32.004 |
| - type: mrr_at_100 |
| value: 32.789 |
| - type: mrr_at_1000 |
| value: 32.857 |
| - type: mrr_at_3 |
| value: 29.084 |
| - type: mrr_at_5 |
| value: 30.614 |
| - type: ndcg_at_1 |
| value: 23.134 |
| - type: ndcg_at_10 |
| value: 32.852 |
| - type: ndcg_at_100 |
| value: 37.972 |
| - type: ndcg_at_1000 |
| value: 40.656 |
| - type: ndcg_at_3 |
| value: 27.435 |
| - type: ndcg_at_5 |
| value: 29.823 |
| - type: precision_at_1 |
| value: 23.134 |
| - type: precision_at_10 |
| value: 6.032 |
| - type: precision_at_100 |
| value: 0.9950000000000001 |
| - type: precision_at_1000 |
| value: 0.136 |
| - type: precision_at_3 |
| value: 13.017999999999999 |
| - type: precision_at_5 |
| value: 9.501999999999999 |
| - type: recall_at_1 |
| value: 18.886 |
| - type: recall_at_10 |
| value: 45.34 |
| - type: recall_at_100 |
| value: 67.947 |
| - type: recall_at_1000 |
| value: 86.924 |
| - type: recall_at_3 |
| value: 30.535 |
| - type: recall_at_5 |
| value: 36.451 |
| - type: map_at_1 |
| value: 28.994999999999997 |
| - type: map_at_10 |
| value: 40.04 |
| - type: map_at_100 |
| value: 41.435 |
| - type: map_at_1000 |
| value: 41.537 |
| - type: map_at_3 |
| value: 37.091 |
| - type: map_at_5 |
| value: 38.802 |
| - type: mrr_at_1 |
| value: 35.034 |
| - type: mrr_at_10 |
| value: 45.411 |
| - type: mrr_at_100 |
| value: 46.226 |
| - type: mrr_at_1000 |
| value: 46.27 |
| - type: mrr_at_3 |
| value: 43.086 |
| - type: mrr_at_5 |
| value: 44.452999999999996 |
| - type: ndcg_at_1 |
| value: 35.034 |
| - type: ndcg_at_10 |
| value: 46.076 |
| - type: ndcg_at_100 |
| value: 51.483000000000004 |
| - type: ndcg_at_1000 |
| value: 53.433 |
| - type: ndcg_at_3 |
| value: 41.304 |
| - type: ndcg_at_5 |
| value: 43.641999999999996 |
| - type: precision_at_1 |
| value: 35.034 |
| - type: precision_at_10 |
| value: 8.258000000000001 |
| - type: precision_at_100 |
| value: 1.268 |
| - type: precision_at_1000 |
| value: 0.161 |
| - type: precision_at_3 |
| value: 19.57 |
| - type: precision_at_5 |
| value: 13.782 |
| - type: recall_at_1 |
| value: 28.994999999999997 |
| - type: recall_at_10 |
| value: 58.538000000000004 |
| - type: recall_at_100 |
| value: 80.72399999999999 |
| - type: recall_at_1000 |
| value: 93.462 |
| - type: recall_at_3 |
| value: 45.199 |
| - type: recall_at_5 |
| value: 51.237 |
| - type: map_at_1 |
| value: 24.795 |
| - type: map_at_10 |
| value: 34.935 |
| - type: map_at_100 |
| value: 36.306 |
| - type: map_at_1000 |
| value: 36.417 |
| - type: map_at_3 |
| value: 31.831 |
| - type: map_at_5 |
| value: 33.626 |
| - type: mrr_at_1 |
| value: 30.479 |
| - type: mrr_at_10 |
| value: 40.225 |
| - type: mrr_at_100 |
| value: 41.055 |
| - type: mrr_at_1000 |
| value: 41.114 |
| - type: mrr_at_3 |
| value: 37.538 |
| - type: mrr_at_5 |
| value: 39.073 |
| - type: ndcg_at_1 |
| value: 30.479 |
| - type: ndcg_at_10 |
| value: 40.949999999999996 |
| - type: ndcg_at_100 |
| value: 46.525 |
| - type: ndcg_at_1000 |
| value: 48.892 |
| - type: ndcg_at_3 |
| value: 35.79 |
| - type: ndcg_at_5 |
| value: 38.237 |
| - type: precision_at_1 |
| value: 30.479 |
| - type: precision_at_10 |
| value: 7.6259999999999994 |
| - type: precision_at_100 |
| value: 1.203 |
| - type: precision_at_1000 |
| value: 0.157 |
| - type: precision_at_3 |
| value: 17.199 |
| - type: precision_at_5 |
| value: 12.466000000000001 |
| - type: recall_at_1 |
| value: 24.795 |
| - type: recall_at_10 |
| value: 53.421 |
| - type: recall_at_100 |
| value: 77.189 |
| - type: recall_at_1000 |
| value: 93.407 |
| - type: recall_at_3 |
| value: 39.051 |
| - type: recall_at_5 |
| value: 45.462 |
| - type: map_at_1 |
| value: 26.853499999999997 |
| - type: map_at_10 |
| value: 36.20433333333333 |
| - type: map_at_100 |
| value: 37.40391666666667 |
| - type: map_at_1000 |
| value: 37.515 |
| - type: map_at_3 |
| value: 33.39975 |
| - type: map_at_5 |
| value: 34.9665 |
| - type: mrr_at_1 |
| value: 31.62666666666667 |
| - type: mrr_at_10 |
| value: 40.436749999999996 |
| - type: mrr_at_100 |
| value: 41.260333333333335 |
| - type: mrr_at_1000 |
| value: 41.31525 |
| - type: mrr_at_3 |
| value: 38.06733333333332 |
| - type: mrr_at_5 |
| value: 39.41541666666667 |
| - type: ndcg_at_1 |
| value: 31.62666666666667 |
| - type: ndcg_at_10 |
| value: 41.63341666666667 |
| - type: ndcg_at_100 |
| value: 46.704166666666666 |
| - type: ndcg_at_1000 |
| value: 48.88483333333335 |
| - type: ndcg_at_3 |
| value: 36.896 |
| - type: ndcg_at_5 |
| value: 39.11891666666667 |
| - type: precision_at_1 |
| value: 31.62666666666667 |
| - type: precision_at_10 |
| value: 7.241083333333333 |
| - type: precision_at_100 |
| value: 1.1488333333333334 |
| - type: precision_at_1000 |
| value: 0.15250000000000002 |
| - type: precision_at_3 |
| value: 16.908333333333335 |
| - type: precision_at_5 |
| value: 11.942833333333333 |
| - type: recall_at_1 |
| value: 26.853499999999997 |
| - type: recall_at_10 |
| value: 53.461333333333336 |
| - type: recall_at_100 |
| value: 75.63633333333333 |
| - type: recall_at_1000 |
| value: 90.67016666666666 |
| - type: recall_at_3 |
| value: 40.24241666666667 |
| - type: recall_at_5 |
| value: 45.98608333333333 |
| - type: map_at_1 |
| value: 25.241999999999997 |
| - type: map_at_10 |
| value: 31.863999999999997 |
| - type: map_at_100 |
| value: 32.835 |
| - type: map_at_1000 |
| value: 32.928000000000004 |
| - type: map_at_3 |
| value: 29.694 |
| - type: map_at_5 |
| value: 30.978 |
| - type: mrr_at_1 |
| value: 28.374 |
| - type: mrr_at_10 |
| value: 34.814 |
| - type: mrr_at_100 |
| value: 35.596 |
| - type: mrr_at_1000 |
| value: 35.666 |
| - type: mrr_at_3 |
| value: 32.745000000000005 |
| - type: mrr_at_5 |
| value: 34.049 |
| - type: ndcg_at_1 |
| value: 28.374 |
| - type: ndcg_at_10 |
| value: 35.969 |
| - type: ndcg_at_100 |
| value: 40.708 |
| - type: ndcg_at_1000 |
| value: 43.08 |
| - type: ndcg_at_3 |
| value: 31.968999999999998 |
| - type: ndcg_at_5 |
| value: 34.069 |
| - type: precision_at_1 |
| value: 28.374 |
| - type: precision_at_10 |
| value: 5.583 |
| - type: precision_at_100 |
| value: 0.8630000000000001 |
| - type: precision_at_1000 |
| value: 0.11299999999999999 |
| - type: precision_at_3 |
| value: 13.547999999999998 |
| - type: precision_at_5 |
| value: 9.447999999999999 |
| - type: recall_at_1 |
| value: 25.241999999999997 |
| - type: recall_at_10 |
| value: 45.711 |
| - type: recall_at_100 |
| value: 67.482 |
| - type: recall_at_1000 |
| value: 85.13300000000001 |
| - type: recall_at_3 |
| value: 34.622 |
| - type: recall_at_5 |
| value: 40.043 |
| - type: map_at_1 |
| value: 17.488999999999997 |
| - type: map_at_10 |
| value: 25.142999999999997 |
| - type: map_at_100 |
| value: 26.244 |
| - type: map_at_1000 |
| value: 26.363999999999997 |
| - type: map_at_3 |
| value: 22.654 |
| - type: map_at_5 |
| value: 24.017 |
| - type: mrr_at_1 |
| value: 21.198 |
| - type: mrr_at_10 |
| value: 28.903000000000002 |
| - type: mrr_at_100 |
| value: 29.860999999999997 |
| - type: mrr_at_1000 |
| value: 29.934 |
| - type: mrr_at_3 |
| value: 26.634999999999998 |
| - type: mrr_at_5 |
| value: 27.903 |
| - type: ndcg_at_1 |
| value: 21.198 |
| - type: ndcg_at_10 |
| value: 29.982999999999997 |
| - type: ndcg_at_100 |
| value: 35.275 |
| - type: ndcg_at_1000 |
| value: 38.074000000000005 |
| - type: ndcg_at_3 |
| value: 25.502999999999997 |
| - type: ndcg_at_5 |
| value: 27.557 |
| - type: precision_at_1 |
| value: 21.198 |
| - type: precision_at_10 |
| value: 5.502 |
| - type: precision_at_100 |
| value: 0.942 |
| - type: precision_at_1000 |
| value: 0.136 |
| - type: precision_at_3 |
| value: 12.044 |
| - type: precision_at_5 |
| value: 8.782 |
| - type: recall_at_1 |
| value: 17.488999999999997 |
| - type: recall_at_10 |
| value: 40.821000000000005 |
| - type: recall_at_100 |
| value: 64.567 |
| - type: recall_at_1000 |
| value: 84.452 |
| - type: recall_at_3 |
| value: 28.351 |
| - type: recall_at_5 |
| value: 33.645 |
| - type: map_at_1 |
| value: 27.066000000000003 |
| - type: map_at_10 |
| value: 36.134 |
| - type: map_at_100 |
| value: 37.285000000000004 |
| - type: map_at_1000 |
| value: 37.389 |
| - type: map_at_3 |
| value: 33.522999999999996 |
| - type: map_at_5 |
| value: 34.905 |
| - type: mrr_at_1 |
| value: 31.436999999999998 |
| - type: mrr_at_10 |
| value: 40.225 |
| - type: mrr_at_100 |
| value: 41.079 |
| - type: mrr_at_1000 |
| value: 41.138000000000005 |
| - type: mrr_at_3 |
| value: 38.074999999999996 |
| - type: mrr_at_5 |
| value: 39.190000000000005 |
| - type: ndcg_at_1 |
| value: 31.436999999999998 |
| - type: ndcg_at_10 |
| value: 41.494 |
| - type: ndcg_at_100 |
| value: 46.678999999999995 |
| - type: ndcg_at_1000 |
| value: 48.964 |
| - type: ndcg_at_3 |
| value: 36.828 |
| - type: ndcg_at_5 |
| value: 38.789 |
| - type: precision_at_1 |
| value: 31.436999999999998 |
| - type: precision_at_10 |
| value: 6.931 |
| - type: precision_at_100 |
| value: 1.072 |
| - type: precision_at_1000 |
| value: 0.13799999999999998 |
| - type: precision_at_3 |
| value: 16.729 |
| - type: precision_at_5 |
| value: 11.567 |
| - type: recall_at_1 |
| value: 27.066000000000003 |
| - type: recall_at_10 |
| value: 53.705000000000005 |
| - type: recall_at_100 |
| value: 75.968 |
| - type: recall_at_1000 |
| value: 91.937 |
| - type: recall_at_3 |
| value: 40.865 |
| - type: recall_at_5 |
| value: 45.739999999999995 |
| - type: map_at_1 |
| value: 24.979000000000003 |
| - type: map_at_10 |
| value: 32.799 |
| - type: map_at_100 |
| value: 34.508 |
| - type: map_at_1000 |
| value: 34.719 |
| - type: map_at_3 |
| value: 29.947000000000003 |
| - type: map_at_5 |
| value: 31.584 |
| - type: mrr_at_1 |
| value: 30.237000000000002 |
| - type: mrr_at_10 |
| value: 37.651 |
| - type: mrr_at_100 |
| value: 38.805 |
| - type: mrr_at_1000 |
| value: 38.851 |
| - type: mrr_at_3 |
| value: 35.046 |
| - type: mrr_at_5 |
| value: 36.548 |
| - type: ndcg_at_1 |
| value: 30.237000000000002 |
| - type: ndcg_at_10 |
| value: 38.356 |
| - type: ndcg_at_100 |
| value: 44.906 |
| - type: ndcg_at_1000 |
| value: 47.299 |
| - type: ndcg_at_3 |
| value: 33.717999999999996 |
| - type: ndcg_at_5 |
| value: 35.946 |
| - type: precision_at_1 |
| value: 30.237000000000002 |
| - type: precision_at_10 |
| value: 7.292 |
| - type: precision_at_100 |
| value: 1.496 |
| - type: precision_at_1000 |
| value: 0.23600000000000002 |
| - type: precision_at_3 |
| value: 15.547 |
| - type: precision_at_5 |
| value: 11.344 |
| - type: recall_at_1 |
| value: 24.979000000000003 |
| - type: recall_at_10 |
| value: 48.624 |
| - type: recall_at_100 |
| value: 77.932 |
| - type: recall_at_1000 |
| value: 92.66499999999999 |
| - type: recall_at_3 |
| value: 35.217 |
| - type: recall_at_5 |
| value: 41.394 |
| - type: map_at_1 |
| value: 22.566 |
| - type: map_at_10 |
| value: 30.945 |
| - type: map_at_100 |
| value: 31.759999999999998 |
| - type: map_at_1000 |
| value: 31.855 |
| - type: map_at_3 |
| value: 28.64 |
| - type: map_at_5 |
| value: 29.787000000000003 |
| - type: mrr_at_1 |
| value: 24.954 |
| - type: mrr_at_10 |
| value: 33.311 |
| - type: mrr_at_100 |
| value: 34.050000000000004 |
| - type: mrr_at_1000 |
| value: 34.117999999999995 |
| - type: mrr_at_3 |
| value: 31.238 |
| - type: mrr_at_5 |
| value: 32.329 |
| - type: ndcg_at_1 |
| value: 24.954 |
| - type: ndcg_at_10 |
| value: 35.676 |
| - type: ndcg_at_100 |
| value: 39.931 |
| - type: ndcg_at_1000 |
| value: 42.43 |
| - type: ndcg_at_3 |
| value: 31.365 |
| - type: ndcg_at_5 |
| value: 33.184999999999995 |
| - type: precision_at_1 |
| value: 24.954 |
| - type: precision_at_10 |
| value: 5.564 |
| - type: precision_at_100 |
| value: 0.826 |
| - type: precision_at_1000 |
| value: 0.116 |
| - type: precision_at_3 |
| value: 13.555 |
| - type: precision_at_5 |
| value: 9.168 |
| - type: recall_at_1 |
| value: 22.566 |
| - type: recall_at_10 |
| value: 47.922 |
| - type: recall_at_100 |
| value: 67.931 |
| - type: recall_at_1000 |
| value: 86.653 |
| - type: recall_at_3 |
| value: 36.103 |
| - type: recall_at_5 |
| value: 40.699000000000005 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB ClimateFEVER |
| type: climate-fever |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 16.950000000000003 |
| - type: map_at_10 |
| value: 28.612 |
| - type: map_at_100 |
| value: 30.476999999999997 |
| - type: map_at_1000 |
| value: 30.674 |
| - type: map_at_3 |
| value: 24.262 |
| - type: map_at_5 |
| value: 26.554 |
| - type: mrr_at_1 |
| value: 38.241 |
| - type: mrr_at_10 |
| value: 50.43 |
| - type: mrr_at_100 |
| value: 51.059 |
| - type: mrr_at_1000 |
| value: 51.090999999999994 |
| - type: mrr_at_3 |
| value: 47.514 |
| - type: mrr_at_5 |
| value: 49.246 |
| - type: ndcg_at_1 |
| value: 38.241 |
| - type: ndcg_at_10 |
| value: 38.218 |
| - type: ndcg_at_100 |
| value: 45.003 |
| - type: ndcg_at_1000 |
| value: 48.269 |
| - type: ndcg_at_3 |
| value: 32.568000000000005 |
| - type: ndcg_at_5 |
| value: 34.400999999999996 |
| - type: precision_at_1 |
| value: 38.241 |
| - type: precision_at_10 |
| value: 11.674 |
| - type: precision_at_100 |
| value: 1.913 |
| - type: precision_at_1000 |
| value: 0.252 |
| - type: precision_at_3 |
| value: 24.387 |
| - type: precision_at_5 |
| value: 18.163 |
| - type: recall_at_1 |
| value: 16.950000000000003 |
| - type: recall_at_10 |
| value: 43.769000000000005 |
| - type: recall_at_100 |
| value: 66.875 |
| - type: recall_at_1000 |
| value: 84.92699999999999 |
| - type: recall_at_3 |
| value: 29.353 |
| - type: recall_at_5 |
| value: 35.467 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB DBPedia |
| type: dbpedia-entity |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 9.276 |
| - type: map_at_10 |
| value: 20.848 |
| - type: map_at_100 |
| value: 29.804000000000002 |
| - type: map_at_1000 |
| value: 31.398 |
| - type: map_at_3 |
| value: 14.886 |
| - type: map_at_5 |
| value: 17.516000000000002 |
| - type: mrr_at_1 |
| value: 71 |
| - type: mrr_at_10 |
| value: 78.724 |
| - type: mrr_at_100 |
| value: 78.976 |
| - type: mrr_at_1000 |
| value: 78.986 |
| - type: mrr_at_3 |
| value: 77.333 |
| - type: mrr_at_5 |
| value: 78.021 |
| - type: ndcg_at_1 |
| value: 57.875 |
| - type: ndcg_at_10 |
| value: 43.855 |
| - type: ndcg_at_100 |
| value: 48.99 |
| - type: ndcg_at_1000 |
| value: 56.141 |
| - type: ndcg_at_3 |
| value: 48.914 |
| - type: ndcg_at_5 |
| value: 45.961 |
| - type: precision_at_1 |
| value: 71 |
| - type: precision_at_10 |
| value: 34.575 |
| - type: precision_at_100 |
| value: 11.182 |
| - type: precision_at_1000 |
| value: 2.044 |
| - type: precision_at_3 |
| value: 52.5 |
| - type: precision_at_5 |
| value: 44.2 |
| - type: recall_at_1 |
| value: 9.276 |
| - type: recall_at_10 |
| value: 26.501 |
| - type: recall_at_100 |
| value: 55.72899999999999 |
| - type: recall_at_1000 |
| value: 78.532 |
| - type: recall_at_3 |
| value: 16.365 |
| - type: recall_at_5 |
| value: 20.154 |
| - task: |
| type: Classification |
| dataset: |
| name: MTEB EmotionClassification |
| type: mteb/emotion |
| config: default |
| split: test |
| revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
| metrics: |
| - type: accuracy |
| value: 52.71 |
| - type: f1 |
| value: 47.74801556489574 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB FEVER |
| type: fever |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 73.405 |
| - type: map_at_10 |
| value: 82.822 |
| - type: map_at_100 |
| value: 83.042 |
| - type: map_at_1000 |
| value: 83.055 |
| - type: map_at_3 |
| value: 81.65299999999999 |
| - type: map_at_5 |
| value: 82.431 |
| - type: mrr_at_1 |
| value: 79.178 |
| - type: mrr_at_10 |
| value: 87.02 |
| - type: mrr_at_100 |
| value: 87.095 |
| - type: mrr_at_1000 |
| value: 87.09700000000001 |
| - type: mrr_at_3 |
| value: 86.309 |
| - type: mrr_at_5 |
| value: 86.824 |
| - type: ndcg_at_1 |
| value: 79.178 |
| - type: ndcg_at_10 |
| value: 86.72 |
| - type: ndcg_at_100 |
| value: 87.457 |
| - type: ndcg_at_1000 |
| value: 87.691 |
| - type: ndcg_at_3 |
| value: 84.974 |
| - type: ndcg_at_5 |
| value: 86.032 |
| - type: precision_at_1 |
| value: 79.178 |
| - type: precision_at_10 |
| value: 10.548 |
| - type: precision_at_100 |
| value: 1.113 |
| - type: precision_at_1000 |
| value: 0.11499999999999999 |
| - type: precision_at_3 |
| value: 32.848 |
| - type: precision_at_5 |
| value: 20.45 |
| - type: recall_at_1 |
| value: 73.405 |
| - type: recall_at_10 |
| value: 94.39699999999999 |
| - type: recall_at_100 |
| value: 97.219 |
| - type: recall_at_1000 |
| value: 98.675 |
| - type: recall_at_3 |
| value: 89.679 |
| - type: recall_at_5 |
| value: 92.392 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB FiQA2018 |
| type: fiqa |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 22.651 |
| - type: map_at_10 |
| value: 36.886 |
| - type: map_at_100 |
| value: 38.811 |
| - type: map_at_1000 |
| value: 38.981 |
| - type: map_at_3 |
| value: 32.538 |
| - type: map_at_5 |
| value: 34.763 |
| - type: mrr_at_1 |
| value: 44.444 |
| - type: mrr_at_10 |
| value: 53.168000000000006 |
| - type: mrr_at_100 |
| value: 53.839000000000006 |
| - type: mrr_at_1000 |
| value: 53.869 |
| - type: mrr_at_3 |
| value: 50.54 |
| - type: mrr_at_5 |
| value: 52.068000000000005 |
| - type: ndcg_at_1 |
| value: 44.444 |
| - type: ndcg_at_10 |
| value: 44.994 |
| - type: ndcg_at_100 |
| value: 51.599 |
| - type: ndcg_at_1000 |
| value: 54.339999999999996 |
| - type: ndcg_at_3 |
| value: 41.372 |
| - type: ndcg_at_5 |
| value: 42.149 |
| - type: precision_at_1 |
| value: 44.444 |
| - type: precision_at_10 |
| value: 12.407 |
| - type: precision_at_100 |
| value: 1.9269999999999998 |
| - type: precision_at_1000 |
| value: 0.242 |
| - type: precision_at_3 |
| value: 27.726 |
| - type: precision_at_5 |
| value: 19.814999999999998 |
| - type: recall_at_1 |
| value: 22.651 |
| - type: recall_at_10 |
| value: 52.075 |
| - type: recall_at_100 |
| value: 76.51400000000001 |
| - type: recall_at_1000 |
| value: 92.852 |
| - type: recall_at_3 |
| value: 37.236000000000004 |
| - type: recall_at_5 |
| value: 43.175999999999995 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB HotpotQA |
| type: hotpotqa |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 40.777 |
| - type: map_at_10 |
| value: 66.79899999999999 |
| - type: map_at_100 |
| value: 67.65299999999999 |
| - type: map_at_1000 |
| value: 67.706 |
| - type: map_at_3 |
| value: 63.352 |
| - type: map_at_5 |
| value: 65.52900000000001 |
| - type: mrr_at_1 |
| value: 81.553 |
| - type: mrr_at_10 |
| value: 86.983 |
| - type: mrr_at_100 |
| value: 87.132 |
| - type: mrr_at_1000 |
| value: 87.136 |
| - type: mrr_at_3 |
| value: 86.156 |
| - type: mrr_at_5 |
| value: 86.726 |
| - type: ndcg_at_1 |
| value: 81.553 |
| - type: ndcg_at_10 |
| value: 74.64 |
| - type: ndcg_at_100 |
| value: 77.459 |
| - type: ndcg_at_1000 |
| value: 78.43 |
| - type: ndcg_at_3 |
| value: 69.878 |
| - type: ndcg_at_5 |
| value: 72.59400000000001 |
| - type: precision_at_1 |
| value: 81.553 |
| - type: precision_at_10 |
| value: 15.654000000000002 |
| - type: precision_at_100 |
| value: 1.783 |
| - type: precision_at_1000 |
| value: 0.191 |
| - type: precision_at_3 |
| value: 45.199 |
| - type: precision_at_5 |
| value: 29.267 |
| - type: recall_at_1 |
| value: 40.777 |
| - type: recall_at_10 |
| value: 78.271 |
| - type: recall_at_100 |
| value: 89.129 |
| - type: recall_at_1000 |
| value: 95.49 |
| - type: recall_at_3 |
| value: 67.79899999999999 |
| - type: recall_at_5 |
| value: 73.167 |
| - task: |
| type: Classification |
| dataset: |
| name: MTEB ImdbClassification |
| type: mteb/imdb |
| config: default |
| split: test |
| revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
| metrics: |
| - type: accuracy |
| value: 93.5064 |
| - type: ap |
| value: 90.25495114444111 |
| - type: f1 |
| value: 93.5012434973381 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB MSMARCO |
| type: msmarco |
| config: default |
| split: dev |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 23.301 |
| - type: map_at_10 |
| value: 35.657 |
| - type: map_at_100 |
| value: 36.797000000000004 |
| - type: map_at_1000 |
| value: 36.844 |
| - type: map_at_3 |
| value: 31.743 |
| - type: map_at_5 |
| value: 34.003 |
| - type: mrr_at_1 |
| value: 23.854 |
| - type: mrr_at_10 |
| value: 36.242999999999995 |
| - type: mrr_at_100 |
| value: 37.32 |
| - type: mrr_at_1000 |
| value: 37.361 |
| - type: mrr_at_3 |
| value: 32.4 |
| - type: mrr_at_5 |
| value: 34.634 |
| - type: ndcg_at_1 |
| value: 23.868000000000002 |
| - type: ndcg_at_10 |
| value: 42.589 |
| - type: ndcg_at_100 |
| value: 48.031 |
| - type: ndcg_at_1000 |
| value: 49.189 |
| - type: ndcg_at_3 |
| value: 34.649 |
| - type: ndcg_at_5 |
| value: 38.676 |
| - type: precision_at_1 |
| value: 23.868000000000002 |
| - type: precision_at_10 |
| value: 6.6850000000000005 |
| - type: precision_at_100 |
| value: 0.9400000000000001 |
| - type: precision_at_1000 |
| value: 0.104 |
| - type: precision_at_3 |
| value: 14.651 |
| - type: precision_at_5 |
| value: 10.834000000000001 |
| - type: recall_at_1 |
| value: 23.301 |
| - type: recall_at_10 |
| value: 63.88700000000001 |
| - type: recall_at_100 |
| value: 88.947 |
| - type: recall_at_1000 |
| value: 97.783 |
| - type: recall_at_3 |
| value: 42.393 |
| - type: recall_at_5 |
| value: 52.036 |
| - task: |
| type: Classification |
| dataset: |
| name: MTEB MTOPDomainClassification (en) |
| type: mteb/mtop_domain |
| config: en |
| split: test |
| revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| metrics: |
| - type: accuracy |
| value: 94.64888280893753 |
| - type: f1 |
| value: 94.41310774203512 |
| - task: |
| type: Classification |
| dataset: |
| name: MTEB MTOPIntentClassification (en) |
| type: mteb/mtop_intent |
| config: en |
| split: test |
| revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| metrics: |
| - type: accuracy |
| value: 79.72184222526221 |
| - type: f1 |
| value: 61.522034067350106 |
| - task: |
| type: Classification |
| dataset: |
| name: MTEB MassiveIntentClassification (en) |
| type: mteb/amazon_massive_intent |
| config: en |
| split: test |
| revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| metrics: |
| - type: accuracy |
| value: 79.60659045057163 |
| - type: f1 |
| value: 77.268649687049 |
| - task: |
| type: Classification |
| dataset: |
| name: MTEB MassiveScenarioClassification (en) |
| type: mteb/amazon_massive_scenario |
| config: en |
| split: test |
| revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| metrics: |
| - type: accuracy |
| value: 81.83254875588432 |
| - type: f1 |
| value: 81.61520635919082 |
| - task: |
| type: Clustering |
| dataset: |
| name: MTEB MedrxivClusteringP2P |
| type: mteb/medrxiv-clustering-p2p |
| config: default |
| split: test |
| revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
| metrics: |
| - type: v_measure |
| value: 36.31529875009507 |
| - task: |
| type: Clustering |
| dataset: |
| name: MTEB MedrxivClusteringS2S |
| type: mteb/medrxiv-clustering-s2s |
| config: default |
| split: test |
| revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
| metrics: |
| - type: v_measure |
| value: 31.734233714415073 |
| - task: |
| type: Reranking |
| dataset: |
| name: MTEB MindSmallReranking |
| type: mteb/mind_small |
| config: default |
| split: test |
| revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
| metrics: |
| - type: map |
| value: 30.994501713009452 |
| - type: mrr |
| value: 32.13512850703073 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB NFCorpus |
| type: nfcorpus |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 6.603000000000001 |
| - type: map_at_10 |
| value: 13.767999999999999 |
| - type: map_at_100 |
| value: 17.197000000000003 |
| - type: map_at_1000 |
| value: 18.615000000000002 |
| - type: map_at_3 |
| value: 10.567 |
| - type: map_at_5 |
| value: 12.078999999999999 |
| - type: mrr_at_1 |
| value: 44.891999999999996 |
| - type: mrr_at_10 |
| value: 53.75299999999999 |
| - type: mrr_at_100 |
| value: 54.35 |
| - type: mrr_at_1000 |
| value: 54.388000000000005 |
| - type: mrr_at_3 |
| value: 51.495999999999995 |
| - type: mrr_at_5 |
| value: 52.688 |
| - type: ndcg_at_1 |
| value: 43.189 |
| - type: ndcg_at_10 |
| value: 34.567 |
| - type: ndcg_at_100 |
| value: 32.273 |
| - type: ndcg_at_1000 |
| value: 41.321999999999996 |
| - type: ndcg_at_3 |
| value: 40.171 |
| - type: ndcg_at_5 |
| value: 37.502 |
| - type: precision_at_1 |
| value: 44.582 |
| - type: precision_at_10 |
| value: 25.139 |
| - type: precision_at_100 |
| value: 7.739999999999999 |
| - type: precision_at_1000 |
| value: 2.054 |
| - type: precision_at_3 |
| value: 37.152 |
| - type: precision_at_5 |
| value: 31.826999999999998 |
| - type: recall_at_1 |
| value: 6.603000000000001 |
| - type: recall_at_10 |
| value: 17.023 |
| - type: recall_at_100 |
| value: 32.914 |
| - type: recall_at_1000 |
| value: 64.44800000000001 |
| - type: recall_at_3 |
| value: 11.457 |
| - type: recall_at_5 |
| value: 13.816 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB NQ |
| type: nq |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 30.026000000000003 |
| - type: map_at_10 |
| value: 45.429 |
| - type: map_at_100 |
| value: 46.45 |
| - type: map_at_1000 |
| value: 46.478 |
| - type: map_at_3 |
| value: 41.147 |
| - type: map_at_5 |
| value: 43.627 |
| - type: mrr_at_1 |
| value: 33.951 |
| - type: mrr_at_10 |
| value: 47.953 |
| - type: mrr_at_100 |
| value: 48.731 |
| - type: mrr_at_1000 |
| value: 48.751 |
| - type: mrr_at_3 |
| value: 44.39 |
| - type: mrr_at_5 |
| value: 46.533 |
| - type: ndcg_at_1 |
| value: 33.951 |
| - type: ndcg_at_10 |
| value: 53.24100000000001 |
| - type: ndcg_at_100 |
| value: 57.599999999999994 |
| - type: ndcg_at_1000 |
| value: 58.270999999999994 |
| - type: ndcg_at_3 |
| value: 45.190999999999995 |
| - type: ndcg_at_5 |
| value: 49.339 |
| - type: precision_at_1 |
| value: 33.951 |
| - type: precision_at_10 |
| value: 8.856 |
| - type: precision_at_100 |
| value: 1.133 |
| - type: precision_at_1000 |
| value: 0.12 |
| - type: precision_at_3 |
| value: 20.713 |
| - type: precision_at_5 |
| value: 14.838000000000001 |
| - type: recall_at_1 |
| value: 30.026000000000003 |
| - type: recall_at_10 |
| value: 74.512 |
| - type: recall_at_100 |
| value: 93.395 |
| - type: recall_at_1000 |
| value: 98.402 |
| - type: recall_at_3 |
| value: 53.677 |
| - type: recall_at_5 |
| value: 63.198 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB QuoraRetrieval |
| type: quora |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 71.41300000000001 |
| - type: map_at_10 |
| value: 85.387 |
| - type: map_at_100 |
| value: 86.027 |
| - type: map_at_1000 |
| value: 86.041 |
| - type: map_at_3 |
| value: 82.543 |
| - type: map_at_5 |
| value: 84.304 |
| - type: mrr_at_1 |
| value: 82.35 |
| - type: mrr_at_10 |
| value: 88.248 |
| - type: mrr_at_100 |
| value: 88.348 |
| - type: mrr_at_1000 |
| value: 88.349 |
| - type: mrr_at_3 |
| value: 87.348 |
| - type: mrr_at_5 |
| value: 87.96300000000001 |
| - type: ndcg_at_1 |
| value: 82.37 |
| - type: ndcg_at_10 |
| value: 88.98 |
| - type: ndcg_at_100 |
| value: 90.16499999999999 |
| - type: ndcg_at_1000 |
| value: 90.239 |
| - type: ndcg_at_3 |
| value: 86.34100000000001 |
| - type: ndcg_at_5 |
| value: 87.761 |
| - type: precision_at_1 |
| value: 82.37 |
| - type: precision_at_10 |
| value: 13.471 |
| - type: precision_at_100 |
| value: 1.534 |
| - type: precision_at_1000 |
| value: 0.157 |
| - type: precision_at_3 |
| value: 37.827 |
| - type: precision_at_5 |
| value: 24.773999999999997 |
| - type: recall_at_1 |
| value: 71.41300000000001 |
| - type: recall_at_10 |
| value: 95.748 |
| - type: recall_at_100 |
| value: 99.69200000000001 |
| - type: recall_at_1000 |
| value: 99.98 |
| - type: recall_at_3 |
| value: 87.996 |
| - type: recall_at_5 |
| value: 92.142 |
| - task: |
| type: Clustering |
| dataset: |
| name: MTEB RedditClustering |
| type: mteb/reddit-clustering |
| config: default |
| split: test |
| revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| metrics: |
| - type: v_measure |
| value: 56.96878497780007 |
| - task: |
| type: Clustering |
| dataset: |
| name: MTEB RedditClusteringP2P |
| type: mteb/reddit-clustering-p2p |
| config: default |
| split: test |
| revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
| metrics: |
| - type: v_measure |
| value: 65.31371347128074 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB SCIDOCS |
| type: scidocs |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 5.287 |
| - type: map_at_10 |
| value: 13.530000000000001 |
| - type: map_at_100 |
| value: 15.891 |
| - type: map_at_1000 |
| value: 16.245 |
| - type: map_at_3 |
| value: 9.612 |
| - type: map_at_5 |
| value: 11.672 |
| - type: mrr_at_1 |
| value: 26 |
| - type: mrr_at_10 |
| value: 37.335 |
| - type: mrr_at_100 |
| value: 38.443 |
| - type: mrr_at_1000 |
| value: 38.486 |
| - type: mrr_at_3 |
| value: 33.783 |
| - type: mrr_at_5 |
| value: 36.028 |
| - type: ndcg_at_1 |
| value: 26 |
| - type: ndcg_at_10 |
| value: 22.215 |
| - type: ndcg_at_100 |
| value: 31.101 |
| - type: ndcg_at_1000 |
| value: 36.809 |
| - type: ndcg_at_3 |
| value: 21.104 |
| - type: ndcg_at_5 |
| value: 18.759999999999998 |
| - type: precision_at_1 |
| value: 26 |
| - type: precision_at_10 |
| value: 11.43 |
| - type: precision_at_100 |
| value: 2.424 |
| - type: precision_at_1000 |
| value: 0.379 |
| - type: precision_at_3 |
| value: 19.7 |
| - type: precision_at_5 |
| value: 16.619999999999997 |
| - type: recall_at_1 |
| value: 5.287 |
| - type: recall_at_10 |
| value: 23.18 |
| - type: recall_at_100 |
| value: 49.208 |
| - type: recall_at_1000 |
| value: 76.85300000000001 |
| - type: recall_at_3 |
| value: 11.991999999999999 |
| - type: recall_at_5 |
| value: 16.85 |
| - task: |
| type: STS |
| dataset: |
| name: MTEB SICK-R |
| type: mteb/sickr-sts |
| config: default |
| split: test |
| revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
| metrics: |
| - type: cos_sim_pearson |
| value: 83.87834913790886 |
| - type: cos_sim_spearman |
| value: 81.04583513112122 |
| - type: euclidean_pearson |
| value: 81.20484174558065 |
| - type: euclidean_spearman |
| value: 80.76430832561769 |
| - type: manhattan_pearson |
| value: 81.21416730978615 |
| - type: manhattan_spearman |
| value: 80.7797637394211 |
| - task: |
| type: STS |
| dataset: |
| name: MTEB STS12 |
| type: mteb/sts12-sts |
| config: default |
| split: test |
| revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| metrics: |
| - type: cos_sim_pearson |
| value: 86.56143998865157 |
| - type: cos_sim_spearman |
| value: 79.75387012744471 |
| - type: euclidean_pearson |
| value: 83.7877519997019 |
| - type: euclidean_spearman |
| value: 79.90489748003296 |
| - type: manhattan_pearson |
| value: 83.7540590666095 |
| - type: manhattan_spearman |
| value: 79.86434577931573 |
| - task: |
| type: STS |
| dataset: |
| name: MTEB STS13 |
| type: mteb/sts13-sts |
| config: default |
| split: test |
| revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| metrics: |
| - type: cos_sim_pearson |
| value: 83.92102564177941 |
| - type: cos_sim_spearman |
| value: 84.98234585939103 |
| - type: euclidean_pearson |
| value: 84.47729567593696 |
| - type: euclidean_spearman |
| value: 85.09490696194469 |
| - type: manhattan_pearson |
| value: 84.38622951588229 |
| - type: manhattan_spearman |
| value: 85.02507171545574 |
| - task: |
| type: STS |
| dataset: |
| name: MTEB STS14 |
| type: mteb/sts14-sts |
| config: default |
| split: test |
| revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| metrics: |
| - type: cos_sim_pearson |
| value: 80.1891164763377 |
| - type: cos_sim_spearman |
| value: 80.7997969966883 |
| - type: euclidean_pearson |
| value: 80.48572256162396 |
| - type: euclidean_spearman |
| value: 80.57851903536378 |
| - type: manhattan_pearson |
| value: 80.4324819433651 |
| - type: manhattan_spearman |
| value: 80.5074526239062 |
| - task: |
| type: STS |
| dataset: |
| name: MTEB STS15 |
| type: mteb/sts15-sts |
| config: default |
| split: test |
| revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| metrics: |
| - type: cos_sim_pearson |
| value: 82.64319975116025 |
| - type: cos_sim_spearman |
| value: 84.88671197763652 |
| - type: euclidean_pearson |
| value: 84.74692193293231 |
| - type: euclidean_spearman |
| value: 85.27151722073653 |
| - type: manhattan_pearson |
| value: 84.72460516785438 |
| - type: manhattan_spearman |
| value: 85.26518899786687 |
| - task: |
| type: STS |
| dataset: |
| name: MTEB STS16 |
| type: mteb/sts16-sts |
| config: default |
| split: test |
| revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| metrics: |
| - type: cos_sim_pearson |
| value: 83.24687565822381 |
| - type: cos_sim_spearman |
| value: 85.60418454111263 |
| - type: euclidean_pearson |
| value: 84.85829740169851 |
| - type: euclidean_spearman |
| value: 85.66378014138306 |
| - type: manhattan_pearson |
| value: 84.84672408808835 |
| - type: manhattan_spearman |
| value: 85.63331924364891 |
| - task: |
| type: STS |
| dataset: |
| name: MTEB STS17 (en-en) |
| type: mteb/sts17-crosslingual-sts |
| config: en-en |
| split: test |
| revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| metrics: |
| - type: cos_sim_pearson |
| value: 84.87758895415485 |
| - type: cos_sim_spearman |
| value: 85.8193745617297 |
| - type: euclidean_pearson |
| value: 85.78719118848134 |
| - type: euclidean_spearman |
| value: 84.35797575385688 |
| - type: manhattan_pearson |
| value: 85.97919844815692 |
| - type: manhattan_spearman |
| value: 84.58334745175151 |
| - task: |
| type: STS |
| dataset: |
| name: MTEB STS22 (en) |
| type: mteb/sts22-crosslingual-sts |
| config: en |
| split: test |
| revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
| metrics: |
| - type: cos_sim_pearson |
| value: 67.27076035963599 |
| - type: cos_sim_spearman |
| value: 67.21433656439973 |
| - type: euclidean_pearson |
| value: 68.07434078679324 |
| - type: euclidean_spearman |
| value: 66.0249731719049 |
| - type: manhattan_pearson |
| value: 67.95495198947476 |
| - type: manhattan_spearman |
| value: 65.99893908331886 |
| - task: |
| type: STS |
| dataset: |
| name: MTEB STSBenchmark |
| type: mteb/stsbenchmark-sts |
| config: default |
| split: test |
| revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
| metrics: |
| - type: cos_sim_pearson |
| value: 82.22437747056817 |
| - type: cos_sim_spearman |
| value: 85.0995685206174 |
| - type: euclidean_pearson |
| value: 84.08616925603394 |
| - type: euclidean_spearman |
| value: 84.89633925691658 |
| - type: manhattan_pearson |
| value: 84.08332675923133 |
| - type: manhattan_spearman |
| value: 84.8858228112915 |
| - task: |
| type: Reranking |
| dataset: |
| name: MTEB SciDocsRR |
| type: mteb/scidocs-reranking |
| config: default |
| split: test |
| revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| metrics: |
| - type: map |
| value: 87.6909022589666 |
| - type: mrr |
| value: 96.43341952165481 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB SciFact |
| type: scifact |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 57.660999999999994 |
| - type: map_at_10 |
| value: 67.625 |
| - type: map_at_100 |
| value: 68.07600000000001 |
| - type: map_at_1000 |
| value: 68.10199999999999 |
| - type: map_at_3 |
| value: 64.50399999999999 |
| - type: map_at_5 |
| value: 66.281 |
| - type: mrr_at_1 |
| value: 61 |
| - type: mrr_at_10 |
| value: 68.953 |
| - type: mrr_at_100 |
| value: 69.327 |
| - type: mrr_at_1000 |
| value: 69.352 |
| - type: mrr_at_3 |
| value: 66.833 |
| - type: mrr_at_5 |
| value: 68.05 |
| - type: ndcg_at_1 |
| value: 61 |
| - type: ndcg_at_10 |
| value: 72.369 |
| - type: ndcg_at_100 |
| value: 74.237 |
| - type: ndcg_at_1000 |
| value: 74.939 |
| - type: ndcg_at_3 |
| value: 67.284 |
| - type: ndcg_at_5 |
| value: 69.72500000000001 |
| - type: precision_at_1 |
| value: 61 |
| - type: precision_at_10 |
| value: 9.733 |
| - type: precision_at_100 |
| value: 1.0670000000000002 |
| - type: precision_at_1000 |
| value: 0.11199999999999999 |
| - type: precision_at_3 |
| value: 26.222 |
| - type: precision_at_5 |
| value: 17.4 |
| - type: recall_at_1 |
| value: 57.660999999999994 |
| - type: recall_at_10 |
| value: 85.656 |
| - type: recall_at_100 |
| value: 93.833 |
| - type: recall_at_1000 |
| value: 99.333 |
| - type: recall_at_3 |
| value: 71.961 |
| - type: recall_at_5 |
| value: 78.094 |
| - task: |
| type: PairClassification |
| dataset: |
| name: MTEB SprintDuplicateQuestions |
| type: mteb/sprintduplicatequestions-pairclassification |
| config: default |
| split: test |
| revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 99.86930693069307 |
| - type: cos_sim_ap |
| value: 96.76685487950894 |
| - type: cos_sim_f1 |
| value: 93.44587884806354 |
| - type: cos_sim_precision |
| value: 92.80078895463511 |
| - type: cos_sim_recall |
| value: 94.1 |
| - type: dot_accuracy |
| value: 99.54356435643564 |
| - type: dot_ap |
| value: 81.18659960405607 |
| - type: dot_f1 |
| value: 75.78008915304605 |
| - type: dot_precision |
| value: 75.07360157016683 |
| - type: dot_recall |
| value: 76.5 |
| - type: euclidean_accuracy |
| value: 99.87326732673267 |
| - type: euclidean_ap |
| value: 96.8102411908941 |
| - type: euclidean_f1 |
| value: 93.6127744510978 |
| - type: euclidean_precision |
| value: 93.42629482071713 |
| - type: euclidean_recall |
| value: 93.8 |
| - type: manhattan_accuracy |
| value: 99.87425742574257 |
| - type: manhattan_ap |
| value: 96.82857341435529 |
| - type: manhattan_f1 |
| value: 93.62129583124059 |
| - type: manhattan_precision |
| value: 94.04641775983855 |
| - type: manhattan_recall |
| value: 93.2 |
| - type: max_accuracy |
| value: 99.87425742574257 |
| - type: max_ap |
| value: 96.82857341435529 |
| - type: max_f1 |
| value: 93.62129583124059 |
| - task: |
| type: Clustering |
| dataset: |
| name: MTEB StackExchangeClustering |
| type: mteb/stackexchange-clustering |
| config: default |
| split: test |
| revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
| metrics: |
| - type: v_measure |
| value: 65.92560972698926 |
| - task: |
| type: Clustering |
| dataset: |
| name: MTEB StackExchangeClusteringP2P |
| type: mteb/stackexchange-clustering-p2p |
| config: default |
| split: test |
| revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
| metrics: |
| - type: v_measure |
| value: 34.92797240259008 |
| - task: |
| type: Reranking |
| dataset: |
| name: MTEB StackOverflowDupQuestions |
| type: mteb/stackoverflowdupquestions-reranking |
| config: default |
| split: test |
| revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
| metrics: |
| - type: map |
| value: 55.244624045597654 |
| - type: mrr |
| value: 56.185303666921314 |
| - task: |
| type: Summarization |
| dataset: |
| name: MTEB SummEval |
| type: mteb/summeval |
| config: default |
| split: test |
| revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c |
| metrics: |
| - type: cos_sim_pearson |
| value: 31.02491987312937 |
| - type: cos_sim_spearman |
| value: 32.055592206679734 |
| - type: dot_pearson |
| value: 24.731627575422557 |
| - type: dot_spearman |
| value: 24.308029077069733 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB TRECCOVID |
| type: trec-covid |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 0.231 |
| - type: map_at_10 |
| value: 1.899 |
| - type: map_at_100 |
| value: 9.498 |
| - type: map_at_1000 |
| value: 20.979999999999997 |
| - type: map_at_3 |
| value: 0.652 |
| - type: map_at_5 |
| value: 1.069 |
| - type: mrr_at_1 |
| value: 88 |
| - type: mrr_at_10 |
| value: 93.4 |
| - type: mrr_at_100 |
| value: 93.4 |
| - type: mrr_at_1000 |
| value: 93.4 |
| - type: mrr_at_3 |
| value: 93 |
| - type: mrr_at_5 |
| value: 93.4 |
| - type: ndcg_at_1 |
| value: 86 |
| - type: ndcg_at_10 |
| value: 75.375 |
| - type: ndcg_at_100 |
| value: 52.891999999999996 |
| - type: ndcg_at_1000 |
| value: 44.952999999999996 |
| - type: ndcg_at_3 |
| value: 81.05 |
| - type: ndcg_at_5 |
| value: 80.175 |
| - type: precision_at_1 |
| value: 88 |
| - type: precision_at_10 |
| value: 79 |
| - type: precision_at_100 |
| value: 53.16 |
| - type: precision_at_1000 |
| value: 19.408 |
| - type: precision_at_3 |
| value: 85.333 |
| - type: precision_at_5 |
| value: 84 |
| - type: recall_at_1 |
| value: 0.231 |
| - type: recall_at_10 |
| value: 2.078 |
| - type: recall_at_100 |
| value: 12.601 |
| - type: recall_at_1000 |
| value: 41.296 |
| - type: recall_at_3 |
| value: 0.6779999999999999 |
| - type: recall_at_5 |
| value: 1.1360000000000001 |
| - task: |
| type: Retrieval |
| dataset: |
| name: MTEB Touche2020 |
| type: webis-touche2020 |
| config: default |
| split: test |
| revision: None |
| metrics: |
| - type: map_at_1 |
| value: 2.782 |
| - type: map_at_10 |
| value: 10.204 |
| - type: map_at_100 |
| value: 16.176 |
| - type: map_at_1000 |
| value: 17.456 |
| - type: map_at_3 |
| value: 5.354 |
| - type: map_at_5 |
| value: 7.503 |
| - type: mrr_at_1 |
| value: 40.816 |
| - type: mrr_at_10 |
| value: 54.010000000000005 |
| - type: mrr_at_100 |
| value: 54.49 |
| - type: mrr_at_1000 |
| value: 54.49 |
| - type: mrr_at_3 |
| value: 48.980000000000004 |
| - type: mrr_at_5 |
| value: 51.735 |
| - type: ndcg_at_1 |
| value: 36.735 |
| - type: ndcg_at_10 |
| value: 26.61 |
| - type: ndcg_at_100 |
| value: 36.967 |
| - type: ndcg_at_1000 |
| value: 47.274 |
| - type: ndcg_at_3 |
| value: 30.363 |
| - type: ndcg_at_5 |
| value: 29.448999999999998 |
| - type: precision_at_1 |
| value: 40.816 |
| - type: precision_at_10 |
| value: 23.878 |
| - type: precision_at_100 |
| value: 7.693999999999999 |
| - type: precision_at_1000 |
| value: 1.4489999999999998 |
| - type: precision_at_3 |
| value: 31.293 |
| - type: precision_at_5 |
| value: 29.796 |
| - type: recall_at_1 |
| value: 2.782 |
| - type: recall_at_10 |
| value: 16.485 |
| - type: recall_at_100 |
| value: 46.924 |
| - type: recall_at_1000 |
| value: 79.365 |
| - type: recall_at_3 |
| value: 6.52 |
| - type: recall_at_5 |
| value: 10.48 |
| - task: |
| type: Classification |
| dataset: |
| name: MTEB ToxicConversationsClassification |
| type: mteb/toxic_conversations_50k |
| config: default |
| split: test |
| revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
| metrics: |
| - type: accuracy |
| value: 70.08300000000001 |
| - type: ap |
| value: 13.91559884590195 |
| - type: f1 |
| value: 53.956838444291364 |
| - task: |
| type: Classification |
| dataset: |
| name: MTEB TweetSentimentExtractionClassification |
| type: mteb/tweet_sentiment_extraction |
| config: default |
| split: test |
| revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| metrics: |
| - type: accuracy |
| value: 59.34069043576683 |
| - type: f1 |
| value: 59.662041994618406 |
| - task: |
| type: Clustering |
| dataset: |
| name: MTEB TwentyNewsgroupsClustering |
| type: mteb/twentynewsgroups-clustering |
| config: default |
| split: test |
| revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| metrics: |
| - type: v_measure |
| value: 53.70780611078653 |
| - task: |
| type: PairClassification |
| dataset: |
| name: MTEB TwitterSemEval2015 |
| type: mteb/twittersemeval2015-pairclassification |
| config: default |
| split: test |
| revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
| metrics: |
| - type: cos_sim_accuracy |
| value: 87.10734934732073 |
| - type: cos_sim_ap |
| value: 77.58349999516054 |
| - type: cos_sim_f1 |
| value: 70.25391395868965 |
| - type: cos_sim_precision |
| value: 70.06035161374967 |
| - type: cos_sim_recall |
| value: 70.44854881266491 |
| - type: dot_accuracy |
| value: 80.60439887941826 |
| - type: dot_ap |
| value: 54.52935200483575 |
| - type: dot_f1 |
| value: 54.170444242973716 |
| - type: dot_precision |
| value: 47.47715534366309 |
| - type: dot_recall |
| value: 63.06068601583114 |
| - type: euclidean_accuracy |
| value: 87.26828396018358 |
| - type: euclidean_ap |
| value: 78.00158454104036 |
| - type: euclidean_f1 |
| value: 70.70292457670601 |
| - type: euclidean_precision |
| value: 68.79680479281079 |
| - type: euclidean_recall |
| value: 72.71767810026385 |
| - type: manhattan_accuracy |
| value: 87.11330988853788 |
| - type: manhattan_ap |
| value: 77.92527099601855 |
| - type: manhattan_f1 |
| value: 70.76488706365502 |
| - type: manhattan_precision |
| value: 68.89055472263868 |
| - type: manhattan_recall |
| value: 72.74406332453826 |
| - type: max_accuracy |
| value: 87.26828396018358 |
| - type: max_ap |
| value: 78.00158454104036 |
| - type: max_f1 |
| value: 70.76488706365502 |
| - task: |
| type: PairClassification |
| dataset: |
| name: MTEB TwitterURLCorpus |
| type: mteb/twitterurlcorpus-pairclassification |
| config: default |
| split: test |
| revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
| metrics: |
| - type: cos_sim_accuracy |
| value: 87.80804905499282 |
| - type: cos_sim_ap |
| value: 83.06187782630936 |
| - type: cos_sim_f1 |
| value: 74.99716435403985 |
| - type: cos_sim_precision |
| value: 73.67951860931579 |
| - type: cos_sim_recall |
| value: 76.36279642747151 |
| - type: dot_accuracy |
| value: 81.83141227151008 |
| - type: dot_ap |
| value: 67.18241090841795 |
| - type: dot_f1 |
| value: 62.216037571751606 |
| - type: dot_precision |
| value: 56.749381227391005 |
| - type: dot_recall |
| value: 68.84816753926701 |
| - type: euclidean_accuracy |
| value: 87.91671517832887 |
| - type: euclidean_ap |
| value: 83.56538942001427 |
| - type: euclidean_f1 |
| value: 75.7327253337256 |
| - type: euclidean_precision |
| value: 72.48856036606828 |
| - type: euclidean_recall |
| value: 79.28087465352634 |
| - type: manhattan_accuracy |
| value: 87.86626304963713 |
| - type: manhattan_ap |
| value: 83.52939841172832 |
| - type: manhattan_f1 |
| value: 75.73635656329888 |
| - type: manhattan_precision |
| value: 72.99150182103836 |
| - type: manhattan_recall |
| value: 78.69571912534647 |
| - type: max_accuracy |
| value: 87.91671517832887 |
| - type: max_ap |
| value: 83.56538942001427 |
| - type: max_f1 |
| value: 75.73635656329888 |
| --- |
| |
| # Sleem247/bge-large-en-Q8_0-GGUF |
| This model was converted to GGUF format from [`BAAI/bge-large-en`](https://huggingface.co/BAAI/bge-large-en) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. |
| Refer to the [original model card](https://huggingface.co/BAAI/bge-large-en) for more details on the model. |
| |
| ## Use with llama.cpp |
| Install llama.cpp through brew (works on Mac and Linux) |
| |
| ```bash |
| brew install llama.cpp |
| |
| ``` |
| Invoke the llama.cpp server or the CLI. |
| |
| ### CLI: |
| ```bash |
| llama-cli --hf-repo Sleem247/bge-large-en-Q8_0-GGUF --hf-file bge-large-en-q8_0.gguf -p "The meaning to life and the universe is" |
| ``` |
| |
| ### Server: |
| ```bash |
| llama-server --hf-repo Sleem247/bge-large-en-Q8_0-GGUF --hf-file bge-large-en-q8_0.gguf -c 2048 |
| ``` |
| |
| Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. |
| |
| Step 1: Clone llama.cpp from GitHub. |
| ``` |
| git clone https://github.com/ggerganov/llama.cpp |
| ``` |
| |
| Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). |
| ``` |
| cd llama.cpp && LLAMA_CURL=1 make |
| ``` |
| |
| Step 3: Run inference through the main binary. |
| ``` |
| ./llama-cli --hf-repo Sleem247/bge-large-en-Q8_0-GGUF --hf-file bge-large-en-q8_0.gguf -p "The meaning to life and the universe is" |
| ``` |
| or |
| ``` |
| ./llama-server --hf-repo Sleem247/bge-large-en-Q8_0-GGUF --hf-file bge-large-en-q8_0.gguf -c 2048 |
| ``` |
| |
