--- tags: - mteb - sparse sparsity quantized onnx embeddings int8 model-index: - name: bge-small-en-v1.5-sparse results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 70.71641791044776 - type: ap value: 32.850850647310004 - type: f1 value: 64.48101916414805 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 83.33962500000001 - type: ap value: 78.28706349240106 - type: f1 value: 83.27426715603062 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 40.988 - type: f1 value: 40.776679545648506 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 26.101999999999997 - type: map_at_10 value: 40.754000000000005 - type: map_at_100 value: 41.83 - type: map_at_1000 value: 41.845 - type: map_at_3 value: 36.178 - type: map_at_5 value: 38.646 - type: mrr_at_1 value: 26.6 - type: mrr_at_10 value: 40.934 - type: mrr_at_100 value: 42.015 - type: mrr_at_1000 value: 42.03 - type: mrr_at_3 value: 36.344 - type: mrr_at_5 value: 38.848 - type: ndcg_at_1 value: 26.101999999999997 - type: ndcg_at_10 value: 49.126999999999995 - type: ndcg_at_100 value: 53.815999999999995 - type: ndcg_at_1000 value: 54.178000000000004 - type: ndcg_at_3 value: 39.607 - type: ndcg_at_5 value: 44.086999999999996 - type: precision_at_1 value: 26.101999999999997 - type: precision_at_10 value: 7.596 - type: precision_at_100 value: 0.967 - type: precision_at_1000 value: 0.099 - type: precision_at_3 value: 16.524 - type: precision_at_5 value: 12.105 - type: recall_at_1 value: 26.101999999999997 - type: recall_at_10 value: 75.96000000000001 - type: recall_at_100 value: 96.65700000000001 - type: recall_at_1000 value: 99.431 - type: recall_at_3 value: 49.573 - type: recall_at_5 value: 60.526 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 43.10651535441929 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 34.41095293826606 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 56.96575970919239 - type: mrr value: 69.92503187794047 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 79.64892774481326 - type: cos_sim_spearman value: 78.953003817029 - type: euclidean_pearson value: 78.92456838230683 - type: euclidean_spearman value: 78.56504316985354 - type: manhattan_pearson value: 79.21436359014227 - type: manhattan_spearman value: 78.66263575501259 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 81.25 - type: f1 value: 81.20841448916138 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 34.69545244587236 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 28.84301739171936 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 23.401 - type: map_at_10 value: 32.451 - type: map_at_100 value: 33.891 - type: map_at_1000 value: 34.01 - type: map_at_3 value: 29.365999999999996 - type: map_at_5 value: 31.240000000000002 - type: mrr_at_1 value: 29.9 - type: mrr_at_10 value: 38.590999999999994 - type: mrr_at_100 value: 39.587 - type: mrr_at_1000 value: 39.637 - type: mrr_at_3 value: 36.028 - type: mrr_at_5 value: 37.673 - type: ndcg_at_1 value: 29.9 - type: ndcg_at_10 value: 38.251000000000005 - type: ndcg_at_100 value: 44.354 - type: ndcg_at_1000 value: 46.642 - type: ndcg_at_3 value: 33.581 - type: ndcg_at_5 value: 35.96 - type: precision_at_1 value: 29.9 - type: precision_at_10 value: 7.439 - type: precision_at_100 value: 1.28 - type: precision_at_1000 value: 0.17700000000000002 - type: precision_at_3 value: 16.404 - type: precision_at_5 value: 12.046 - type: recall_at_1 value: 23.401 - type: recall_at_10 value: 49.305 - type: recall_at_100 value: 75.885 - type: recall_at_1000 value: 90.885 - type: recall_at_3 value: 35.341 - type: recall_at_5 value: 42.275 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 22.103 - type: map_at_10 value: 29.271 - type: map_at_100 value: 30.151 - type: map_at_1000 value: 30.276999999999997 - type: map_at_3 value: 27.289 - type: map_at_5 value: 28.236 - type: mrr_at_1 value: 26.943 - type: mrr_at_10 value: 33.782000000000004 - type: mrr_at_100 value: 34.459 - type: mrr_at_1000 value: 34.525 - type: mrr_at_3 value: 31.985000000000003 - type: mrr_at_5 value: 32.909 - type: ndcg_at_1 value: 26.943 - type: ndcg_at_10 value: 33.616 - type: ndcg_at_100 value: 37.669000000000004 - type: ndcg_at_1000 value: 40.247 - type: ndcg_at_3 value: 30.482 - type: ndcg_at_5 value: 31.615 - type: precision_at_1 value: 26.943 - type: precision_at_10 value: 6.146 - type: precision_at_100 value: 1.038 - type: precision_at_1000 value: 0.151 - type: precision_at_3 value: 14.521999999999998 - type: precision_at_5 value: 10.038 - type: recall_at_1 value: 22.103 - type: recall_at_10 value: 41.754999999999995 - type: recall_at_100 value: 59.636 - type: recall_at_1000 value: 76.801 - type: recall_at_3 value: 32.285000000000004 - type: recall_at_5 value: 35.684 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 32.565 - type: map_at_10 value: 43.07 - type: map_at_100 value: 44.102999999999994 - type: map_at_1000 value: 44.175 - type: map_at_3 value: 40.245 - type: map_at_5 value: 41.71 - type: mrr_at_1 value: 37.429 - type: mrr_at_10 value: 46.358 - type: mrr_at_100 value: 47.146 - type: mrr_at_1000 value: 47.187 - type: mrr_at_3 value: 44.086 - type: mrr_at_5 value: 45.318000000000005 - type: ndcg_at_1 value: 37.429 - type: ndcg_at_10 value: 48.398 - type: ndcg_at_100 value: 52.90899999999999 - type: ndcg_at_1000 value: 54.478 - type: ndcg_at_3 value: 43.418 - type: ndcg_at_5 value: 45.578 - type: precision_at_1 value: 37.429 - type: precision_at_10 value: 7.856000000000001 - type: precision_at_100 value: 1.093 - type: precision_at_1000 value: 0.129 - type: precision_at_3 value: 19.331 - type: precision_at_5 value: 13.191 - type: recall_at_1 value: 32.565 - type: recall_at_10 value: 61.021 - type: recall_at_100 value: 81.105 - type: recall_at_1000 value: 92.251 - type: recall_at_3 value: 47.637 - type: recall_at_5 value: 52.871 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 18.108 - type: map_at_10 value: 24.613 - type: map_at_100 value: 25.624000000000002 - type: map_at_1000 value: 25.721 - type: map_at_3 value: 22.271 - type: map_at_5 value: 23.681 - type: mrr_at_1 value: 19.435 - type: mrr_at_10 value: 26.124000000000002 - type: mrr_at_100 value: 27.07 - type: mrr_at_1000 value: 27.145999999999997 - type: mrr_at_3 value: 23.748 - type: mrr_at_5 value: 25.239 - type: ndcg_at_1 value: 19.435 - type: ndcg_at_10 value: 28.632 - type: ndcg_at_100 value: 33.988 - type: ndcg_at_1000 value: 36.551 - type: ndcg_at_3 value: 24.035999999999998 - type: ndcg_at_5 value: 26.525 - type: precision_at_1 value: 19.435 - type: precision_at_10 value: 4.565 - type: precision_at_100 value: 0.771 - type: precision_at_1000 value: 0.10200000000000001 - type: precision_at_3 value: 10.169 - type: precision_at_5 value: 7.571 - type: recall_at_1 value: 18.108 - type: recall_at_10 value: 39.533 - type: recall_at_100 value: 64.854 - type: recall_at_1000 value: 84.421 - type: recall_at_3 value: 27.500000000000004 - type: recall_at_5 value: 33.314 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 11.087 - type: map_at_10 value: 17.323 - type: map_at_100 value: 18.569 - type: map_at_1000 value: 18.694 - type: map_at_3 value: 15.370000000000001 - type: map_at_5 value: 16.538 - type: mrr_at_1 value: 13.557 - type: mrr_at_10 value: 21.041 - type: mrr_at_100 value: 22.134 - type: mrr_at_1000 value: 22.207 - type: mrr_at_3 value: 18.843 - type: mrr_at_5 value: 20.236 - type: ndcg_at_1 value: 13.557 - type: ndcg_at_10 value: 21.571 - type: ndcg_at_100 value: 27.678000000000004 - type: ndcg_at_1000 value: 30.8 - type: ndcg_at_3 value: 17.922 - type: ndcg_at_5 value: 19.826 - type: precision_at_1 value: 13.557 - type: precision_at_10 value: 4.1290000000000004 - type: precision_at_100 value: 0.8370000000000001 - type: precision_at_1000 value: 0.125 - type: precision_at_3 value: 8.914 - type: precision_at_5 value: 6.691999999999999 - type: recall_at_1 value: 11.087 - type: recall_at_10 value: 30.94 - type: recall_at_100 value: 57.833999999999996 - type: recall_at_1000 value: 80.365 - type: recall_at_3 value: 20.854 - type: recall_at_5 value: 25.695 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 21.708 - type: map_at_10 value: 30.422 - type: map_at_100 value: 31.713 - type: map_at_1000 value: 31.842 - type: map_at_3 value: 27.424 - type: map_at_5 value: 29.17 - type: mrr_at_1 value: 26.756 - type: mrr_at_10 value: 35.304 - type: mrr_at_100 value: 36.296 - type: mrr_at_1000 value: 36.359 - type: mrr_at_3 value: 32.692 - type: mrr_at_5 value: 34.288999999999994 - type: ndcg_at_1 value: 26.756 - type: ndcg_at_10 value: 35.876000000000005 - type: ndcg_at_100 value: 41.708 - type: ndcg_at_1000 value: 44.359 - type: ndcg_at_3 value: 30.946 - type: ndcg_at_5 value: 33.404 - type: precision_at_1 value: 26.756 - type: precision_at_10 value: 6.795 - type: precision_at_100 value: 1.138 - type: precision_at_1000 value: 0.155 - type: precision_at_3 value: 15.046999999999999 - type: precision_at_5 value: 10.972 - type: recall_at_1 value: 21.708 - type: recall_at_10 value: 47.315000000000005 - type: recall_at_100 value: 72.313 - type: recall_at_1000 value: 90.199 - type: recall_at_3 value: 33.528999999999996 - type: recall_at_5 value: 39.985 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 18.902 - type: map_at_10 value: 26.166 - type: map_at_100 value: 27.368 - type: map_at_1000 value: 27.493000000000002 - type: map_at_3 value: 23.505000000000003 - type: map_at_5 value: 25.019000000000002 - type: mrr_at_1 value: 23.402 - type: mrr_at_10 value: 30.787 - type: mrr_at_100 value: 31.735000000000003 - type: mrr_at_1000 value: 31.806 - type: mrr_at_3 value: 28.33 - type: mrr_at_5 value: 29.711 - type: ndcg_at_1 value: 23.402 - type: ndcg_at_10 value: 30.971 - type: ndcg_at_100 value: 36.61 - type: ndcg_at_1000 value: 39.507999999999996 - type: ndcg_at_3 value: 26.352999999999998 - type: ndcg_at_5 value: 28.488000000000003 - type: precision_at_1 value: 23.402 - type: precision_at_10 value: 5.799 - type: precision_at_100 value: 1.0 - type: precision_at_1000 value: 0.14100000000000001 - type: precision_at_3 value: 12.633 - type: precision_at_5 value: 9.269 - type: recall_at_1 value: 18.902 - type: recall_at_10 value: 40.929 - type: recall_at_100 value: 65.594 - type: recall_at_1000 value: 85.961 - type: recall_at_3 value: 28.121000000000002 - type: recall_at_5 value: 33.638 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 19.168 - type: map_at_10 value: 25.142999999999997 - type: map_at_100 value: 25.993 - type: map_at_1000 value: 26.076 - type: map_at_3 value: 23.179 - type: map_at_5 value: 24.322 - type: mrr_at_1 value: 21.933 - type: mrr_at_10 value: 27.72 - type: mrr_at_100 value: 28.518 - type: mrr_at_1000 value: 28.582 - type: mrr_at_3 value: 25.791999999999998 - type: mrr_at_5 value: 26.958 - type: ndcg_at_1 value: 21.933 - type: ndcg_at_10 value: 28.866999999999997 - type: ndcg_at_100 value: 33.285 - type: ndcg_at_1000 value: 35.591 - type: ndcg_at_3 value: 25.202999999999996 - type: ndcg_at_5 value: 27.045 - type: precision_at_1 value: 21.933 - type: precision_at_10 value: 4.632 - type: precision_at_100 value: 0.733 - type: precision_at_1000 value: 0.101 - type: precision_at_3 value: 10.992 - type: precision_at_5 value: 7.853000000000001 - type: recall_at_1 value: 19.168 - type: recall_at_10 value: 37.899 - type: recall_at_100 value: 58.54899999999999 - type: recall_at_1000 value: 75.666 - type: recall_at_3 value: 27.831 - type: recall_at_5 value: 32.336 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 12.764000000000001 - type: map_at_10 value: 17.757 - type: map_at_100 value: 18.677 - type: map_at_1000 value: 18.813 - type: map_at_3 value: 16.151 - type: map_at_5 value: 16.946 - type: mrr_at_1 value: 15.726 - type: mrr_at_10 value: 21.019 - type: mrr_at_100 value: 21.856 - type: mrr_at_1000 value: 21.954 - type: mrr_at_3 value: 19.282 - type: mrr_at_5 value: 20.189 - type: ndcg_at_1 value: 15.726 - type: ndcg_at_10 value: 21.259 - type: ndcg_at_100 value: 25.868999999999996 - type: ndcg_at_1000 value: 29.425 - type: ndcg_at_3 value: 18.204 - type: ndcg_at_5 value: 19.434 - type: precision_at_1 value: 15.726 - type: precision_at_10 value: 3.8920000000000003 - type: precision_at_100 value: 0.741 - type: precision_at_1000 value: 0.121 - type: precision_at_3 value: 8.58 - type: precision_at_5 value: 6.132 - type: recall_at_1 value: 12.764000000000001 - type: recall_at_10 value: 28.639 - type: recall_at_100 value: 49.639 - type: recall_at_1000 value: 75.725 - type: recall_at_3 value: 19.883 - type: recall_at_5 value: 23.141000000000002 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 18.98 - type: map_at_10 value: 25.2 - type: map_at_100 value: 26.279000000000003 - type: map_at_1000 value: 26.399 - type: map_at_3 value: 23.399 - type: map_at_5 value: 24.284 - type: mrr_at_1 value: 22.015 - type: mrr_at_10 value: 28.555000000000003 - type: mrr_at_100 value: 29.497 - type: mrr_at_1000 value: 29.574 - type: mrr_at_3 value: 26.788 - type: mrr_at_5 value: 27.576 - type: ndcg_at_1 value: 22.015 - type: ndcg_at_10 value: 29.266 - type: ndcg_at_100 value: 34.721000000000004 - type: ndcg_at_1000 value: 37.659 - type: ndcg_at_3 value: 25.741000000000003 - type: ndcg_at_5 value: 27.044 - type: precision_at_1 value: 22.015 - type: precision_at_10 value: 4.897 - type: precision_at_100 value: 0.8540000000000001 - type: precision_at_1000 value: 0.122 - type: precision_at_3 value: 11.567 - type: precision_at_5 value: 7.9479999999999995 - type: recall_at_1 value: 18.98 - type: recall_at_10 value: 38.411 - type: recall_at_100 value: 63.164 - type: recall_at_1000 value: 84.292 - type: recall_at_3 value: 28.576 - type: recall_at_5 value: 31.789 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 20.372 - type: map_at_10 value: 27.161 - type: map_at_100 value: 28.364 - type: map_at_1000 value: 28.554000000000002 - type: map_at_3 value: 25.135 - type: map_at_5 value: 26.200000000000003 - type: mrr_at_1 value: 24.704 - type: mrr_at_10 value: 31.219 - type: mrr_at_100 value: 32.092 - type: mrr_at_1000 value: 32.181 - type: mrr_at_3 value: 29.282000000000004 - type: mrr_at_5 value: 30.359 - type: ndcg_at_1 value: 24.704 - type: ndcg_at_10 value: 31.622 - type: ndcg_at_100 value: 36.917 - type: ndcg_at_1000 value: 40.357 - type: ndcg_at_3 value: 28.398 - type: ndcg_at_5 value: 29.764000000000003 - type: precision_at_1 value: 24.704 - type: precision_at_10 value: 5.81 - type: precision_at_100 value: 1.208 - type: precision_at_1000 value: 0.209 - type: precision_at_3 value: 13.241 - type: precision_at_5 value: 9.407 - type: recall_at_1 value: 20.372 - type: recall_at_10 value: 40.053 - type: recall_at_100 value: 64.71000000000001 - type: recall_at_1000 value: 87.607 - type: recall_at_3 value: 29.961 - type: recall_at_5 value: 34.058 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 14.424000000000001 - type: map_at_10 value: 20.541999999999998 - type: map_at_100 value: 21.495 - type: map_at_1000 value: 21.604 - type: map_at_3 value: 18.608 - type: map_at_5 value: 19.783 - type: mrr_at_1 value: 15.895999999999999 - type: mrr_at_10 value: 22.484 - type: mrr_at_100 value: 23.376 - type: mrr_at_1000 value: 23.467 - type: mrr_at_3 value: 20.548 - type: mrr_at_5 value: 21.731 - type: ndcg_at_1 value: 15.895999999999999 - type: ndcg_at_10 value: 24.343 - type: ndcg_at_100 value: 29.181 - type: ndcg_at_1000 value: 32.330999999999996 - type: ndcg_at_3 value: 20.518 - type: ndcg_at_5 value: 22.561999999999998 - type: precision_at_1 value: 15.895999999999999 - type: precision_at_10 value: 3.9739999999999998 - type: precision_at_100 value: 0.6799999999999999 - type: precision_at_1000 value: 0.105 - type: precision_at_3 value: 9.057 - type: precision_at_5 value: 6.654 - type: recall_at_1 value: 14.424000000000001 - type: recall_at_10 value: 34.079 - type: recall_at_100 value: 56.728 - type: recall_at_1000 value: 80.765 - type: recall_at_3 value: 23.993000000000002 - type: recall_at_5 value: 28.838 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - type: accuracy value: 41.665 - type: f1 value: 37.601137843331244 - task: type: Classification dataset: type: mteb/imdb name: MTEB ImdbClassification config: default split: test revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 metrics: - type: accuracy value: 74.8052 - type: ap value: 68.92588517572685 - type: f1 value: 74.66801685854456 - task: type: Classification dataset: type: mteb/mtop_domain name: MTEB MTOPDomainClassification (en) config: en split: test revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf metrics: - type: accuracy value: 91.2220702234382 - type: f1 value: 90.81687856852439 - task: type: Classification dataset: type: mteb/mtop_intent name: MTEB MTOPIntentClassification (en) config: en split: test revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba metrics: - type: accuracy value: 69.39124487004105 - type: f1 value: 51.8350043424968 - task: type: Classification dataset: type: mteb/amazon_massive_intent name: MTEB MassiveIntentClassification (en) config: en split: test revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 metrics: - type: accuracy value: 69.80497646267652 - type: f1 value: 67.34213899244814 - task: type: Classification dataset: type: mteb/amazon_massive_scenario name: MTEB MassiveScenarioClassification (en) config: en split: test revision: 7d571f92784cd94a019292a1f45445077d0ef634 metrics: - type: accuracy value: 74.54270342972428 - type: f1 value: 74.02802500235784 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-p2p name: MTEB MedrxivClusteringP2P config: default split: test revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 metrics: - type: v_measure value: 30.488580544269002 - task: type: Clustering dataset: type: mteb/medrxiv-clustering-s2s name: MTEB MedrxivClusteringS2S config: default split: test revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 metrics: - type: v_measure value: 28.80426879476371 - task: type: Reranking dataset: type: mteb/mind_small name: MTEB MindSmallReranking config: default split: test revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 metrics: - type: map value: 31.37970068676043 - type: mrr value: 32.48523694064166 - task: type: Clustering dataset: type: mteb/reddit-clustering name: MTEB RedditClustering config: default split: test revision: 24640382cdbf8abc73003fb0fa6d111a705499eb metrics: - type: v_measure value: 42.862710845031565 - 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type: euclidean_ap value: 84.22633217661986 - type: euclidean_f1 value: 76.09190339866403 - type: euclidean_precision value: 72.70304390517605 - type: euclidean_recall value: 79.81213427779488 - type: manhattan_accuracy value: 88.08359529630924 - type: manhattan_ap value: 84.18362004611083 - type: manhattan_f1 value: 76.08789625360231 - type: manhattan_precision value: 71.49336582724072 - type: manhattan_recall value: 81.3135201724669 - type: max_accuracy value: 88.08359529630924 - type: max_ap value: 84.22633217661986 - type: max_f1 value: 76.09190339866403 license: mit language: - en --- # bge-small-en-v1.5-sparse ## Usage This is the sparse ONNX variant of the [bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) embeddings model accelerated with [Sparsify](https://github.com/neuralmagic/sparsify) for quantization/pruning and [DeepSparseSentenceTransformers](https://github.com/neuralmagic/deepsparse/tree/main/src/deepsparse/sentence_transformers) for inference. ```bash pip install -U deepsparse-nightly[sentence_transformers] ``` ```python from deepsparse.sentence_transformers import DeepSparseSentenceTransformer model = DeepSparseSentenceTransformer('neuralmagic/bge-small-en-v1.5-sparse', export=False) # Our sentences we like to encode sentences = ['This framework generates embeddings for each input sentence', 'Sentences are passed as a list of string.', 'The quick brown fox jumps over the lazy dog.'] # Sentences are encoded by calling model.encode() embeddings = model.encode(sentences) # Print the embeddings for sentence, embedding in zip(sentences, embeddings): print("Sentence:", sentence) print("Embedding:", embedding.shape) print("") ``` For general questions on these models and sparsification methods, reach out to the engineering team on our [community Slack](https://join.slack.com/t/discuss-neuralmagic/shared_invite/zt-q1a1cnvo-YBoICSIw3L1dmQpjBeDurQ).