diff --git "a/README.md" "b/README.md" new file mode 100644--- /dev/null +++ "b/README.md" @@ -0,0 +1,21124 @@ +--- +pipeline_tag: sentence-similarity +tags: +- sentence-transformers +- feature-extraction +- sentence-similarity +- mteb +- transformers.js +- mlx +license: apache-2.0 +language: +- en +base_model: +- answerdotai/ModernBERT-base +- nomic-ai/modernbert-embed-unsupervised +base_model_relation: finetune +model-index: +- name: binarize_False + results: + - task: + type: Classification + dataset: + name: MTEB AmazonCounterfactualClassification (en) + type: None + config: en + split: test + revision: e8379541af4e31359cca9fbcf4b00f2671dba205 + metrics: + - type: accuracy + value: 78.13432835820896 + - type: ap + value: 42.190424731303246 + - type: f1 + value: 72.34446401534811 + - task: + type: Classification + dataset: + name: MTEB AmazonPolarityClassification + type: None + config: default + split: test + revision: e2d317d38cd51312af73b3d32a06d1a08b442046 + metrics: + - type: accuracy + value: 93.093825 + - type: ap + value: 90.03727505544286 + - type: f1 + value: 93.0874055138833 + - task: + type: Classification + dataset: + name: MTEB AmazonReviewsClassification (en) + type: None + config: en + split: test + revision: 1399c76144fd37290681b995c656ef9b2e06e26d + metrics: + - type: accuracy + value: 48.428000000000004 + - type: f1 + value: 47.74311520203536 + - task: + type: Retrieval + dataset: + name: MTEB ArguAna + type: None + config: default + split: test + revision: c22ab2a51041ffd869aaddef7af8d8215647e41a + metrics: + - type: map_at_1 + value: 23.898 + - type: map_at_10 + value: 39.775 + - type: map_at_100 + value: 40.827000000000005 + - type: map_at_1000 + value: 40.837 + - type: map_at_20 + value: 40.604 + - type: map_at_3 + value: 34.519 + - type: map_at_5 + value: 37.307 + - type: mrr_at_1 + value: 24.395 + - type: mrr_at_10 + value: 39.963 + - type: mrr_at_100 + value: 41.014 + - type: mrr_at_1000 + value: 41.024 + - type: mrr_at_20 + value: 40.791 + - type: mrr_at_3 + value: 34.732 + - type: mrr_at_5 + value: 37.480999999999995 + - type: ndcg_at_1 + value: 23.898 + - type: ndcg_at_10 + value: 48.962 + - type: ndcg_at_100 + value: 53.386 + - type: ndcg_at_1000 + value: 53.634 + - type: ndcg_at_20 + value: 51.898999999999994 + - type: ndcg_at_3 + value: 38.034 + - type: ndcg_at_5 + value: 43.036 + - type: precision_at_1 + value: 23.898 + - type: precision_at_10 + value: 7.852 + - type: precision_at_100 + value: 0.9769999999999999 + - type: precision_at_1000 + value: 0.1 + - type: precision_at_20 + value: 4.4990000000000006 + - type: precision_at_3 + value: 16.073999999999998 + - type: precision_at_5 + value: 12.063 + - type: recall_at_1 + value: 23.898 + - type: recall_at_10 + value: 78.521 + - type: recall_at_100 + value: 97.724 + - type: recall_at_1000 + value: 99.644 + - type: recall_at_20 + value: 89.972 + - type: recall_at_3 + value: 48.222 + - type: recall_at_5 + value: 60.313 + - task: + type: Clustering + dataset: + name: MTEB ArxivClusteringP2P + type: None + config: default + split: test + revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d + metrics: + - 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type: mrr_at_5 + value: 56.38999999999999 + - type: ndcg_at_1 + value: 47.524 + - type: ndcg_at_10 + value: 59.41499999999999 + - type: ndcg_at_100 + value: 63.258 + - type: ndcg_at_1000 + value: 64.376 + - type: ndcg_at_20 + value: 61.149 + - type: ndcg_at_3 + value: 54.381 + - type: ndcg_at_5 + value: 56.89999999999999 + - type: precision_at_1 + value: 47.524 + - type: precision_at_10 + value: 9.386 + - type: precision_at_100 + value: 1.221 + - type: precision_at_1000 + value: 0.136 + - type: precision_at_20 + value: 5.223 + - type: precision_at_3 + value: 24.096 + - type: precision_at_5 + value: 16.364 + - type: recall_at_1 + value: 41.644999999999996 + - type: recall_at_10 + value: 72.386 + - type: recall_at_100 + value: 88.794 + - type: recall_at_1000 + value: 96.75399999999999 + - type: recall_at_20 + value: 78.74 + - type: recall_at_3 + value: 59.028000000000006 + - type: recall_at_5 + value: 65.197 + - task: + type: Retrieval + dataset: + name: MTEB CQADupstackGisRetrieval + type: BeIR/cqadupstack + config: default + split: test + revision: 5003b3064772da1887988e05400cf3806fe491f2 + metrics: + - type: map_at_1 + value: 28.648 + - type: map_at_10 + value: 36.388999999999996 + - type: map_at_100 + value: 37.372 + - type: map_at_1000 + value: 37.457 + - type: map_at_20 + value: 36.912 + - type: map_at_3 + value: 34.076 + - type: map_at_5 + value: 35.415 + - type: mrr_at_1 + value: 30.508000000000003 + - type: mrr_at_10 + value: 38.132 + - type: mrr_at_100 + value: 39.04 + - type: mrr_at_1000 + value: 39.106 + - type: mrr_at_20 + value: 38.643 + - type: mrr_at_3 + value: 35.876000000000005 + - type: mrr_at_5 + value: 37.208999999999996 + - type: ndcg_at_1 + value: 30.508000000000003 + - type: ndcg_at_10 + value: 40.762 + - type: ndcg_at_100 + value: 45.732 + - type: ndcg_at_1000 + value: 47.799 + - type: ndcg_at_20 + value: 42.591 + - type: ndcg_at_3 + value: 36.266999999999996 + - type: ndcg_at_5 + value: 38.58 + - type: precision_at_1 + value: 30.508000000000003 + - type: precision_at_10 + value: 6.010999999999999 + - type: precision_at_100 + value: 0.897 + - type: precision_at_1000 + value: 0.11100000000000002 + - type: precision_at_20 + value: 3.412 + - type: precision_at_3 + value: 14.991 + - type: precision_at_5 + value: 10.328 + - type: recall_at_1 + value: 28.648 + - type: recall_at_10 + value: 52.342999999999996 + - type: recall_at_100 + value: 75.268 + - type: recall_at_1000 + value: 90.641 + - type: recall_at_20 + value: 59.303 + - type: recall_at_3 + value: 40.447 + - type: recall_at_5 + value: 46.117000000000004 + - task: + type: Retrieval + dataset: + name: MTEB CQADupstackMathematicaRetrieval + type: BeIR/cqadupstack + config: default + split: test + revision: 90fceea13679c63fe563ded68f3b6f06e50061de + metrics: + - type: map_at_1 + value: 18.476 + - type: map_at_10 + value: 27.148 + - type: map_at_100 + value: 28.317999999999998 + - type: map_at_1000 + value: 28.427999999999997 + - type: map_at_20 + value: 27.764 + - type: map_at_3 + value: 24.801000000000002 + - type: map_at_5 + value: 26.133 + - type: mrr_at_1 + value: 22.886 + - type: mrr_at_10 + value: 31.741000000000003 + - type: mrr_at_100 + value: 32.708 + - type: mrr_at_1000 + value: 32.769 + - type: mrr_at_20 + value: 32.296 + - type: mrr_at_3 + value: 29.498 + - type: mrr_at_5 + value: 30.773 + - type: ndcg_at_1 + value: 22.886 + - type: ndcg_at_10 + value: 32.265 + - type: ndcg_at_100 + value: 37.829 + - type: ndcg_at_1000 + value: 40.558 + - type: ndcg_at_20 + value: 34.372 + - type: ndcg_at_3 + value: 28.105000000000004 + - type: ndcg_at_5 + value: 30.04 + - type: precision_at_1 + value: 22.886 + - type: precision_at_10 + value: 5.808 + - type: precision_at_100 + value: 0.985 + - type: precision_at_1000 + value: 0.13699999999999998 + - type: precision_at_20 + value: 3.495 + - type: precision_at_3 + value: 13.639999999999999 + - type: precision_at_5 + value: 9.577 + - type: recall_at_1 + value: 18.476 + - type: recall_at_10 + value: 43.442 + - type: recall_at_100 + value: 67.376 + - type: recall_at_1000 + value: 86.874 + - type: recall_at_20 + value: 51.038 + - type: recall_at_3 + value: 31.785999999999998 + - type: recall_at_5 + value: 36.858999999999995 + - task: + type: Retrieval + dataset: + name: MTEB CQADupstackPhysicsRetrieval + type: BeIR/cqadupstack + config: default + split: test + revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4 + metrics: + - type: map_at_1 + value: 29.098000000000003 + - type: map_at_10 + value: 38.97 + - type: map_at_100 + value: 40.293 + - type: map_at_1000 + value: 40.397 + - type: map_at_20 + value: 39.778999999999996 + - type: map_at_3 + value: 35.723 + - type: map_at_5 + value: 37.519999999999996 + - type: mrr_at_1 + value: 35.515 + - type: mrr_at_10 + value: 44.55 + - type: mrr_at_100 + value: 45.37 + - type: mrr_at_1000 + value: 45.412 + - type: mrr_at_20 + value: 45.054 + - type: mrr_at_3 + value: 41.835 + - type: mrr_at_5 + value: 43.356 + - type: ndcg_at_1 + value: 35.515 + - type: ndcg_at_10 + value: 44.91 + - type: ndcg_at_100 + value: 50.27700000000001 + - type: ndcg_at_1000 + value: 52.215 + - type: ndcg_at_20 + value: 47.235 + - type: ndcg_at_3 + value: 39.505 + - type: ndcg_at_5 + value: 42.016 + - type: precision_at_1 + value: 35.515 + - type: precision_at_10 + value: 8.152 + - type: precision_at_100 + value: 1.262 + - type: precision_at_1000 + value: 0.16 + - type: precision_at_20 + value: 4.851 + - type: precision_at_3 + value: 18.447 + - type: precision_at_5 + value: 13.321 + - type: recall_at_1 + value: 29.098000000000003 + - type: recall_at_10 + value: 57.115 + - type: recall_at_100 + value: 79.467 + - type: recall_at_1000 + value: 92.162 + - type: recall_at_20 + value: 65.161 + - type: recall_at_3 + value: 42.254000000000005 + - type: recall_at_5 + value: 48.415 + - task: + type: Retrieval + dataset: + name: MTEB CQADupstackProgrammersRetrieval + type: BeIR/cqadupstack + config: default + split: test + revision: 6184bc1440d2dbc7612be22b50686b8826d22b32 + metrics: + - type: map_at_1 + value: 27.372000000000003 + - type: map_at_10 + value: 37.781 + - type: map_at_100 + value: 39.128 + - type: map_at_1000 + value: 39.238 + - type: map_at_20 + value: 38.592 + - type: map_at_3 + value: 34.782999999999994 + - type: map_at_5 + value: 36.466 + - type: mrr_at_1 + value: 33.904 + - type: mrr_at_10 + value: 43.15 + - type: mrr_at_100 + value: 44.049 + - type: mrr_at_1000 + value: 44.107 + - type: mrr_at_20 + value: 43.721 + - type: mrr_at_3 + value: 40.677 + - type: mrr_at_5 + value: 42.19 + - type: ndcg_at_1 + value: 33.904 + - type: ndcg_at_10 + value: 43.527 + - type: ndcg_at_100 + value: 49.004999999999995 + - type: ndcg_at_1000 + value: 51.276999999999994 + - type: ndcg_at_20 + value: 45.988 + - type: ndcg_at_3 + value: 38.824999999999996 + - type: ndcg_at_5 + value: 41.04 + - type: precision_at_1 + value: 33.904 + - type: precision_at_10 + value: 7.854 + - type: precision_at_100 + value: 1.2309999999999999 + - type: precision_at_1000 + value: 0.16 + - type: precision_at_20 + value: 4.692 + - type: precision_at_3 + value: 18.531 + - type: precision_at_5 + value: 13.150999999999998 + - type: recall_at_1 + value: 27.372000000000003 + - type: recall_at_10 + value: 55.245999999999995 + - type: recall_at_100 + value: 78.278 + - type: recall_at_1000 + value: 93.718 + - type: recall_at_20 + value: 64.095 + - type: recall_at_3 + value: 41.665 + - type: recall_at_5 + value: 47.632000000000005 + - task: + type: Retrieval + dataset: + name: MTEB CQADupstackStatsRetrieval + type: BeIR/cqadupstack + config: default + split: test + revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a + metrics: + - type: map_at_1 + value: 25.653 + - type: map_at_10 + value: 32.151 + - type: map_at_100 + value: 33.152 + - type: map_at_1000 + value: 33.243 + - type: map_at_20 + value: 32.717 + - type: map_at_3 + value: 30.287 + - type: map_at_5 + value: 31.25 + - type: mrr_at_1 + value: 28.988000000000003 + - type: mrr_at_10 + value: 35.131 + - type: mrr_at_100 + value: 36.002 + - type: mrr_at_1000 + value: 36.069 + - type: mrr_at_20 + value: 35.61 + - type: mrr_at_3 + value: 33.308 + - type: mrr_at_5 + value: 34.259 + - type: ndcg_at_1 + value: 28.988000000000003 + - type: ndcg_at_10 + value: 35.988 + - type: ndcg_at_100 + value: 40.764 + - type: ndcg_at_1000 + value: 43.112 + - type: ndcg_at_20 + value: 37.852999999999994 + - type: ndcg_at_3 + value: 32.562000000000005 + - type: ndcg_at_5 + value: 33.983000000000004 + - type: precision_at_1 + value: 28.988000000000003 + - type: precision_at_10 + value: 5.475 + - type: precision_at_100 + value: 0.8500000000000001 + - type: precision_at_1000 + value: 0.11199999999999999 + - type: precision_at_20 + value: 3.229 + - type: precision_at_3 + value: 13.905999999999999 + - type: precision_at_5 + value: 9.386999999999999 + - type: recall_at_1 + value: 25.653 + - type: recall_at_10 + value: 44.962 + - type: recall_at_100 + value: 66.405 + - type: recall_at_1000 + value: 83.88799999999999 + - type: recall_at_20 + value: 51.79899999999999 + - type: recall_at_3 + value: 35.144999999999996 + - type: recall_at_5 + value: 38.814 + - task: + type: Retrieval + dataset: + name: MTEB CQADupstackTexRetrieval + type: BeIR/cqadupstack + config: default + split: test + revision: 46989137a86843e03a6195de44b09deda022eec7 + metrics: + - type: map_at_1 + value: 17.825 + - type: map_at_10 + value: 25.592 + - type: map_at_100 + value: 26.613999999999997 + - type: map_at_1000 + value: 26.734 + - type: map_at_20 + value: 26.115 + - type: map_at_3 + value: 23.119 + - type: map_at_5 + value: 24.54 + - type: mrr_at_1 + value: 21.335 + - type: mrr_at_10 + value: 29.165000000000003 + - type: mrr_at_100 + value: 30.049 + - type: mrr_at_1000 + value: 30.121 + - type: mrr_at_20 + value: 29.639 + - type: mrr_at_3 + value: 26.863999999999997 + - type: mrr_at_5 + value: 28.185 + - type: ndcg_at_1 + value: 21.335 + - type: ndcg_at_10 + value: 30.357 + - type: ndcg_at_100 + value: 35.410000000000004 + - type: ndcg_at_1000 + value: 38.24 + - type: ndcg_at_20 + value: 32.08 + - type: ndcg_at_3 + value: 25.95 + - type: ndcg_at_5 + value: 28.081 + - type: precision_at_1 + value: 21.335 + - type: precision_at_10 + value: 5.506 + - type: precision_at_100 + value: 0.928 + - type: precision_at_1000 + value: 0.135 + - type: precision_at_20 + value: 3.2550000000000003 + - type: precision_at_3 + value: 12.239 + - type: precision_at_5 + value: 8.885 + - type: recall_at_1 + value: 17.825 + - type: recall_at_10 + value: 41.105999999999995 + - type: recall_at_100 + value: 64.17 + - type: recall_at_1000 + value: 84.19200000000001 + - type: recall_at_20 + value: 47.497 + - type: recall_at_3 + value: 28.862 + - type: recall_at_5 + value: 34.348 + - task: + type: Retrieval + dataset: + name: MTEB CQADupstackUnixRetrieval + type: BeIR/cqadupstack + config: default + split: test + revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53 + metrics: + - type: map_at_1 + value: 29.435 + - type: map_at_10 + value: 38.261 + - type: map_at_100 + value: 39.242 + - type: map_at_1000 + value: 39.347 + - type: map_at_20 + value: 38.742 + - type: map_at_3 + value: 35.457 + - type: map_at_5 + value: 37.043 + - type: mrr_at_1 + value: 34.235 + - type: mrr_at_10 + value: 42.24 + - type: mrr_at_100 + value: 42.988 + - type: mrr_at_1000 + value: 43.043 + - type: mrr_at_20 + value: 42.613 + - type: mrr_at_3 + value: 39.832 + - type: mrr_at_5 + value: 41.227000000000004 + - type: ndcg_at_1 + value: 34.235 + - type: ndcg_at_10 + value: 43.384 + - type: ndcg_at_100 + value: 48.14 + - type: ndcg_at_1000 + value: 50.414 + - type: ndcg_at_20 + value: 44.913 + - type: ndcg_at_3 + value: 38.454 + - type: ndcg_at_5 + value: 40.776 + - type: precision_at_1 + value: 34.235 + - type: precision_at_10 + value: 7.164 + - type: precision_at_100 + value: 1.065 + - type: precision_at_1000 + value: 0.13699999999999998 + - type: precision_at_20 + value: 4.021 + - type: precision_at_3 + value: 17.226 + - type: precision_at_5 + value: 12.071 + - type: recall_at_1 + value: 29.435 + - type: recall_at_10 + value: 54.93900000000001 + - type: recall_at_100 + value: 76.176 + - type: recall_at_1000 + value: 91.989 + - type: recall_at_20 + value: 60.451 + - type: recall_at_3 + value: 41.332 + - type: recall_at_5 + value: 47.316 + - task: + type: Retrieval + dataset: + name: MTEB CQADupstackWebmastersRetrieval + type: BeIR/cqadupstack + config: default + split: test + revision: 160c094312a0e1facb97e55eeddb698c0abe3571 + metrics: + - type: map_at_1 + value: 25.605 + - type: map_at_10 + value: 34.162 + - type: map_at_100 + value: 35.827999999999996 + - type: map_at_1000 + value: 36.04 + - type: map_at_20 + value: 35.016000000000005 + - type: map_at_3 + value: 30.984 + - type: map_at_5 + value: 32.717 + - type: mrr_at_1 + value: 30.435000000000002 + - type: mrr_at_10 + value: 38.681 + - type: mrr_at_100 + value: 39.656000000000006 + - type: mrr_at_1000 + value: 39.71 + - type: mrr_at_20 + value: 39.208999999999996 + - type: mrr_at_3 + value: 35.903 + - type: mrr_at_5 + value: 37.454 + - type: ndcg_at_1 + value: 30.435000000000002 + - type: ndcg_at_10 + value: 39.916000000000004 + - type: ndcg_at_100 + value: 45.958 + - type: ndcg_at_1000 + value: 48.449999999999996 + - type: ndcg_at_20 + value: 42.085 + - type: ndcg_at_3 + value: 34.696 + - type: ndcg_at_5 + value: 37.147000000000006 + - type: precision_at_1 + value: 30.435000000000002 + - type: precision_at_10 + value: 7.767 + - type: precision_at_100 + value: 1.547 + - type: precision_at_1000 + value: 0.23800000000000002 + - type: precision_at_20 + value: 4.941 + - type: precision_at_3 + value: 16.073999999999998 + - type: precision_at_5 + value: 11.937000000000001 + - type: recall_at_1 + value: 25.605 + - type: recall_at_10 + value: 50.654999999999994 + - type: recall_at_100 + value: 77.609 + - type: recall_at_1000 + value: 93.518 + - type: recall_at_20 + value: 58.845000000000006 + - type: recall_at_3 + value: 36.272 + - type: recall_at_5 + value: 42.596000000000004 + - task: + type: Retrieval + dataset: + name: MTEB CQADupstackWordpressRetrieval + type: BeIR/cqadupstack + config: default + split: test + revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4 + metrics: + - type: map_at_1 + value: 23.666 + - type: map_at_10 + value: 30.980999999999998 + - type: map_at_100 + value: 32.0 + - type: map_at_1000 + value: 32.098 + - type: map_at_20 + value: 31.621 + - type: map_at_3 + value: 28.449999999999996 + - type: map_at_5 + value: 29.731999999999996 + - type: mrr_at_1 + value: 25.692999999999998 + - type: mrr_at_10 + value: 32.788000000000004 + - type: mrr_at_100 + value: 33.783 + - type: mrr_at_1000 + value: 33.849000000000004 + - type: mrr_at_20 + value: 33.408 + - type: mrr_at_3 + value: 30.561 + - type: mrr_at_5 + value: 31.716 + - type: ndcg_at_1 + value: 25.692999999999998 + - type: ndcg_at_10 + value: 35.428 + - type: ndcg_at_100 + value: 40.375 + - type: ndcg_at_1000 + value: 42.802 + - type: ndcg_at_20 + value: 37.621 + - type: ndcg_at_3 + value: 30.476999999999997 + - type: ndcg_at_5 + value: 32.621 + - type: precision_at_1 + value: 25.692999999999998 + - type: precision_at_10 + value: 5.508 + - type: precision_at_100 + value: 0.848 + - type: precision_at_1000 + value: 0.116 + - type: precision_at_20 + value: 3.272 + - type: precision_at_3 + value: 12.631 + - type: precision_at_5 + value: 8.872 + - type: recall_at_1 + value: 23.666 + - type: recall_at_10 + value: 47.532000000000004 + - type: recall_at_100 + value: 69.73700000000001 + - 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type: cos_sim_accuracy + value: 85.75430649102938 + - type: cos_sim_ap + value: 73.62842656477649 + - type: cos_sim_f1 + value: 67.76023680315738 + - type: cos_sim_precision + value: 63.61741547012506 + - type: cos_sim_recall + value: 72.4802110817942 + - type: dot_accuracy + value: 85.7423854085951 + - type: dot_ap + value: 73.59147637253723 + - type: dot_f1 + value: 67.69498693867396 + - type: dot_precision + value: 64.03859731701577 + - type: dot_recall + value: 71.79419525065963 + - type: euclidean_accuracy + value: 85.7423854085951 + - type: euclidean_ap + value: 73.6288990409654 + - type: euclidean_f1 + value: 67.80415430267064 + - type: euclidean_precision + value: 63.79711493718009 + - type: euclidean_recall + value: 72.34828496042216 + - type: manhattan_accuracy + value: 85.69470107885796 + - type: manhattan_ap + value: 73.49219614602531 + - type: manhattan_f1 + value: 67.60809797550613 + - type: manhattan_precision + value: 64.22127255460589 + - type: manhattan_recall + value: 71.37203166226914 + - type: max_accuracy + value: 85.75430649102938 + - type: max_ap + value: 73.6288990409654 + - type: max_f1 + value: 67.80415430267064 + - task: + type: PairClassification + dataset: + name: MTEB TwitterURLCorpus + type: None + config: default + split: test + revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf + metrics: + - type: cos_sim_accuracy + value: 89.08293553770326 + - type: cos_sim_ap + value: 86.21246419992926 + - type: cos_sim_f1 + value: 78.49922526377924 + - type: cos_sim_precision + value: 75.35769939084857 + - type: cos_sim_recall + value: 81.9140745303357 + - type: dot_accuracy + value: 89.08681647067955 + - type: dot_ap + value: 86.19733517196862 + - type: dot_f1 + value: 78.51132446157838 + - type: dot_precision + value: 75.70233755093287 + - type: dot_recall + value: 81.53680320295658 + - type: euclidean_accuracy + value: 89.07517367175069 + - type: euclidean_ap + value: 86.21198725320203 + - type: euclidean_f1 + value: 78.49867139061116 + - type: euclidean_precision + value: 75.38276155372839 + - type: euclidean_recall + value: 81.88327687095781 + - type: manhattan_accuracy + value: 89.0538285403811 + - type: manhattan_ap + value: 86.17785515765131 + - type: manhattan_f1 + value: 78.48184098593084 + - type: manhattan_precision + value: 74.34396308285694 + - type: manhattan_recall + value: 83.10748383122882 + - type: max_accuracy + value: 89.08681647067955 + - type: max_ap + value: 86.21246419992926 + - type: max_f1 + value: 78.51132446157838 +--- + +# mlx-community/nomicai-modernbert-embed-base-4bit + +The Model [mlx-community/nomicai-modernbert-embed-base-4bit](https://huggingface.co/mlx-community/nomicai-modernbert-embed-base-4bit) was converted to MLX format from [nomic-ai/modernbert-embed-base](https://huggingface.co/nomic-ai/modernbert-embed-base) using mlx-lm version **0.0.3**. + +## Use with mlx + +```bash +pip install mlx-embeddings +``` + +```python +from mlx_embeddings import load, generate +import mlx.core as mx + +model, tokenizer = load("mlx-community/nomicai-modernbert-embed-base-4bit") + +# For text embeddings +output = generate(model, processor, texts=["I like grapes", "I like fruits"]) +embeddings = output.text_embeds # Normalized embeddings + +# Compute dot product between normalized embeddings +similarity_matrix = mx.matmul(embeddings, embeddings.T) + +print("Similarity matrix between texts:") +print(similarity_matrix) + + +```