Upload 5 files

1_Pooling/config.json

@@ -0,0 +1,9 @@
+{
+  "word_embedding_dimension": 768,
+  "pooling_mode_cls_token": false,
+  "pooling_mode_mean_tokens": true,
+  "pooling_mode_max_tokens": false,
+  "pooling_mode_mean_sqrt_len_tokens": false,
+  "pooling_mode_weightedmean_tokens": false,
+  "pooling_mode_lasttoken": false
+}

README.md

@@ -1,3 +1,2752 @@
 ---
+library_name: sentence-transformers
+pipeline_tag: sentence-similarity
+tags:
+  - feature-extraction
+  - sentence-similarity
+  - mteb
+  - transformers
+  - transformers.js
+model-index:
+- name: epoch_0_model
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 76.8507462686567
+    - type: ap
+      value: 40.592189159090495
+    - type: f1
+      value: 71.01634655512476
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 91.51892500000001
+    - type: ap
+      value: 88.50346762975335
+    - type: f1
+      value: 91.50342077459624
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 47.364
+    - type: f1
+      value: 46.72708080922794
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.178
+    - type: map_at_10
+      value: 40.244
+    - type: map_at_100
+      value: 41.321999999999996
+    - type: map_at_1000
+      value: 41.331
+    - type: map_at_3
+      value: 35.016999999999996
+    - type: map_at_5
+      value: 37.99
+    - type: mrr_at_1
+      value: 25.605
+    - type: mrr_at_10
+      value: 40.422000000000004
+    - type: mrr_at_100
+      value: 41.507
+    - type: mrr_at_1000
+      value: 41.516
+    - type: mrr_at_3
+      value: 35.23
+    - type: mrr_at_5
+      value: 38.15
+    - type: ndcg_at_1
+      value: 25.178
+    - type: ndcg_at_10
+      value: 49.258
+    - type: ndcg_at_100
+      value: 53.776
+    - type: ndcg_at_1000
+      value: 53.995000000000005
+    - type: ndcg_at_3
+      value: 38.429
+    - type: ndcg_at_5
+      value: 43.803
+    - type: precision_at_1
+      value: 25.178
+    - type: precision_at_10
+      value: 7.831
+    - type: precision_at_100
+      value: 0.979
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 16.121
+    - type: precision_at_5
+      value: 12.29
+    - type: recall_at_1
+      value: 25.178
+    - type: recall_at_10
+      value: 78.307
+    - type: recall_at_100
+      value: 97.866
+    - type: recall_at_1000
+      value: 99.57300000000001
+    - type: recall_at_3
+      value: 48.364000000000004
+    - type: recall_at_5
+      value: 61.451
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 45.93034494751465
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 36.64579480054327
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 60.601310529222054
+    - type: mrr
+      value: 75.04484896451656
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 88.57797718095814
+    - type: cos_sim_spearman
+      value: 86.47064499110101
+    - type: euclidean_pearson
+      value: 87.4559602783142
+    - type: euclidean_spearman
+      value: 86.47064499110101
+    - type: manhattan_pearson
+      value: 87.7232764230245
+    - type: manhattan_spearman
+      value: 86.91222131777742
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 84.5422077922078
+    - type: f1
+      value: 84.47657456950589
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 38.48953561974464
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 32.75995857510105
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 30.008000000000003
+    - type: map_at_10
+      value: 39.51
+    - type: map_at_100
+      value: 40.841
+    - type: map_at_1000
+      value: 40.973
+    - type: map_at_3
+      value: 36.248999999999995
+    - type: map_at_5
+      value: 38.096999999999994
+    - type: mrr_at_1
+      value: 36.481
+    - type: mrr_at_10
+      value: 44.818000000000005
+    - type: mrr_at_100
+      value: 45.64
+    - type: mrr_at_1000
+      value: 45.687
+    - type: mrr_at_3
+      value: 42.036
+    - type: mrr_at_5
+      value: 43.782
+    - type: ndcg_at_1
+      value: 36.481
+    - type: ndcg_at_10
+      value: 45.152
+    - type: ndcg_at_100
+      value: 50.449
+    - type: ndcg_at_1000
+      value: 52.76499999999999
+    - type: ndcg_at_3
+      value: 40.161
+    - type: ndcg_at_5
+      value: 42.577999999999996
+    - type: precision_at_1
+      value: 36.481
+    - type: precision_at_10
+      value: 8.369
+    - type: precision_at_100
+      value: 1.373
+    - type: precision_at_1000
+      value: 0.186
+    - type: precision_at_3
+      value: 18.693
+    - type: precision_at_5
+      value: 13.533999999999999
+    - type: recall_at_1
+      value: 30.008000000000003
+    - type: recall_at_10
+      value: 56.108999999999995
+    - type: recall_at_100
+      value: 78.55499999999999
+    - type: recall_at_1000
+      value: 93.659
+    - type: recall_at_3
+      value: 41.754999999999995
+    - type: recall_at_5
+      value: 48.296
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 30.262
+    - type: map_at_10
+      value: 40.139
+    - type: map_at_100
+      value: 41.394
+    - type: map_at_1000
+      value: 41.526
+    - type: map_at_3
+      value: 37.155
+    - type: map_at_5
+      value: 38.785
+    - type: mrr_at_1
+      value: 38.153
+    - type: mrr_at_10
+      value: 46.369
+    - type: mrr_at_100
+      value: 47.072
+    - type: mrr_at_1000
+      value: 47.111999999999995
+    - type: mrr_at_3
+      value: 44.268
+    - type: mrr_at_5
+      value: 45.389
+    - type: ndcg_at_1
+      value: 38.153
+    - type: ndcg_at_10
+      value: 45.925
+    - type: ndcg_at_100
+      value: 50.394000000000005
+    - type: ndcg_at_1000
+      value: 52.37500000000001
+    - type: ndcg_at_3
+      value: 41.754000000000005
+    - type: ndcg_at_5
+      value: 43.574
+    - type: precision_at_1
+      value: 38.153
+    - type: precision_at_10
+      value: 8.796
+    - type: precision_at_100
+      value: 1.432
+    - type: precision_at_1000
+      value: 0.189
+    - type: precision_at_3
+      value: 20.318
+    - type: precision_at_5
+      value: 14.395
+    - type: recall_at_1
+      value: 30.262
+    - type: recall_at_10
+      value: 55.72200000000001
+    - type: recall_at_100
+      value: 74.97500000000001
+    - type: recall_at_1000
+      value: 87.342
+    - type: recall_at_3
+      value: 43.129
+    - type: recall_at_5
+      value: 48.336
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 39.951
+    - type: map_at_10
+      value: 51.248000000000005
+    - type: map_at_100
+      value: 52.188
+    - type: map_at_1000
+      value: 52.247
+    - type: map_at_3
+      value: 48.211
+    - type: map_at_5
+      value: 49.797000000000004
+    - type: mrr_at_1
+      value: 45.329
+    - type: mrr_at_10
+      value: 54.749
+    - type: mrr_at_100
+      value: 55.367999999999995
+    - type: mrr_at_1000
+      value: 55.400000000000006
+    - type: mrr_at_3
+      value: 52.382
+    - type: mrr_at_5
+      value: 53.649
+    - type: ndcg_at_1
+      value: 45.329
+    - type: ndcg_at_10
+      value: 56.847
+    - type: ndcg_at_100
+      value: 60.738
+    - type: ndcg_at_1000
+      value: 61.976
+    - type: ndcg_at_3
+      value: 51.59
+    - type: ndcg_at_5
+      value: 53.915
+    - type: precision_at_1
+      value: 45.329
+    - type: precision_at_10
+      value: 8.959
+    - type: precision_at_100
+      value: 1.187
+    - type: precision_at_1000
+      value: 0.134
+    - type: precision_at_3
+      value: 22.612
+    - type: precision_at_5
+      value: 15.273
+    - type: recall_at_1
+      value: 39.951
+    - type: recall_at_10
+      value: 70.053
+    - type: recall_at_100
+      value: 86.996
+    - type: recall_at_1000
+      value: 95.707
+    - type: recall_at_3
+      value: 56.032000000000004
+    - type: recall_at_5
+      value: 61.629999999999995
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.566
+    - type: map_at_10
+      value: 33.207
+    - type: map_at_100
+      value: 34.166000000000004
+    - type: map_at_1000
+      value: 34.245
+    - type: map_at_3
+      value: 30.94
+    - type: map_at_5
+      value: 32.01
+    - type: mrr_at_1
+      value: 27.345000000000002
+    - type: mrr_at_10
+      value: 35.193000000000005
+    - type: mrr_at_100
+      value: 35.965
+    - type: mrr_at_1000
+      value: 36.028999999999996
+    - type: mrr_at_3
+      value: 32.806000000000004
+    - type: mrr_at_5
+      value: 34.021
+    - type: ndcg_at_1
+      value: 27.345000000000002
+    - type: ndcg_at_10
+      value: 37.891999999999996
+    - type: ndcg_at_100
+      value: 42.664
+    - type: ndcg_at_1000
+      value: 44.757000000000005
+    - type: ndcg_at_3
+      value: 33.123000000000005
+    - type: ndcg_at_5
+      value: 35.035
+    - type: precision_at_1
+      value: 27.345000000000002
+    - type: precision_at_10
+      value: 5.763
+    - type: precision_at_100
+      value: 0.859
+    - type: precision_at_1000
+      value: 0.108
+    - type: precision_at_3
+      value: 13.71
+    - type: precision_at_5
+      value: 9.401
+    - type: recall_at_1
+      value: 25.566
+    - type: recall_at_10
+      value: 50.563
+    - type: recall_at_100
+      value: 72.86399999999999
+    - type: recall_at_1000
+      value: 88.68599999999999
+    - type: recall_at_3
+      value: 37.43
+    - type: recall_at_5
+      value: 41.894999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 16.663
+    - type: map_at_10
+      value: 23.552
+    - type: map_at_100
+      value: 24.538
+    - type: map_at_1000
+      value: 24.661
+    - type: map_at_3
+      value: 21.085
+    - type: map_at_5
+      value: 22.391
+    - type: mrr_at_1
+      value: 20.025000000000002
+    - type: mrr_at_10
+      value: 27.643
+    - type: mrr_at_100
+      value: 28.499999999999996
+    - type: mrr_at_1000
+      value: 28.582
+    - type: mrr_at_3
+      value: 25.083
+    - type: mrr_at_5
+      value: 26.544
+    - type: ndcg_at_1
+      value: 20.025000000000002
+    - type: ndcg_at_10
+      value: 28.272000000000002
+    - type: ndcg_at_100
+      value: 33.353
+    - type: ndcg_at_1000
+      value: 36.454
+    - type: ndcg_at_3
+      value: 23.579
+    - type: ndcg_at_5
+      value: 25.685000000000002
+    - type: precision_at_1
+      value: 20.025000000000002
+    - type: precision_at_10
+      value: 5.187
+    - type: precision_at_100
+      value: 0.897
+    - type: precision_at_1000
+      value: 0.13
+    - type: precision_at_3
+      value: 10.987
+    - type: precision_at_5
+      value: 8.06
+    - type: recall_at_1
+      value: 16.663
+    - type: recall_at_10
+      value: 38.808
+    - type: recall_at_100
+      value: 61.305
+    - type: recall_at_1000
+      value: 83.571
+    - type: recall_at_3
+      value: 25.907999999999998
+    - type: recall_at_5
+      value: 31.214
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 27.695999999999998
+    - type: map_at_10
+      value: 37.018
+    - type: map_at_100
+      value: 38.263000000000005
+    - type: map_at_1000
+      value: 38.371
+    - type: map_at_3
+      value: 34.226
+    - type: map_at_5
+      value: 35.809999999999995
+    - type: mrr_at_1
+      value: 32.916000000000004
+    - type: mrr_at_10
+      value: 42.067
+    - type: mrr_at_100
+      value: 42.925000000000004
+    - type: mrr_at_1000
+      value: 42.978
+    - type: mrr_at_3
+      value: 39.637
+    - type: mrr_at_5
+      value: 41.134
+    - type: ndcg_at_1
+      value: 32.916000000000004
+    - type: ndcg_at_10
+      value: 42.539
+    - type: ndcg_at_100
+      value: 47.873
+    - type: ndcg_at_1000
+      value: 50.08200000000001
+    - type: ndcg_at_3
+      value: 37.852999999999994
+    - type: ndcg_at_5
+      value: 40.201
+    - type: precision_at_1
+      value: 32.916000000000004
+    - type: precision_at_10
+      value: 7.5840000000000005
+    - type: precision_at_100
+      value: 1.199
+    - type: precision_at_1000
+      value: 0.155
+    - type: precision_at_3
+      value: 17.485
+    - type: precision_at_5
+      value: 12.512
+    - type: recall_at_1
+      value: 27.695999999999998
+    - type: recall_at_10
+      value: 53.638
+    - type: recall_at_100
+      value: 76.116
+    - type: recall_at_1000
+      value: 91.069
+    - type: recall_at_3
+      value: 41.13
+    - type: recall_at_5
+      value: 46.872
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.108
+    - type: map_at_10
+      value: 33.372
+    - type: map_at_100
+      value: 34.656
+    - type: map_at_1000
+      value: 34.768
+    - type: map_at_3
+      value: 30.830999999999996
+    - type: map_at_5
+      value: 32.204
+    - type: mrr_at_1
+      value: 29.110000000000003
+    - type: mrr_at_10
+      value: 37.979
+    - type: mrr_at_100
+      value: 38.933
+    - type: mrr_at_1000
+      value: 38.988
+    - type: mrr_at_3
+      value: 35.731
+    - type: mrr_at_5
+      value: 36.963
+    - type: ndcg_at_1
+      value: 29.110000000000003
+    - type: ndcg_at_10
+      value: 38.635000000000005
+    - type: ndcg_at_100
+      value: 44.324999999999996
+    - type: ndcg_at_1000
+      value: 46.747
+    - type: ndcg_at_3
+      value: 34.37
+    - type: ndcg_at_5
+      value: 36.228
+    - type: precision_at_1
+      value: 29.110000000000003
+    - type: precision_at_10
+      value: 6.963
+    - type: precision_at_100
+      value: 1.146
+    - type: precision_at_1000
+      value: 0.152
+    - type: precision_at_3
+      value: 16.400000000000002
+    - type: precision_at_5
+      value: 11.552999999999999
+    - type: recall_at_1
+      value: 24.108
+    - type: recall_at_10
+      value: 49.597
+    - type: recall_at_100
+      value: 73.88900000000001
+    - type: recall_at_1000
+      value: 90.62400000000001
+    - type: recall_at_3
+      value: 37.662
+    - type: recall_at_5
+      value: 42.565
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.00791666666667
+    - type: map_at_10
+      value: 33.287749999999996
+    - type: map_at_100
+      value: 34.41141666666667
+    - type: map_at_1000
+      value: 34.52583333333333
+    - type: map_at_3
+      value: 30.734416666666668
+    - type: map_at_5
+      value: 32.137166666666666
+    - type: mrr_at_1
+      value: 29.305666666666664
+    - type: mrr_at_10
+      value: 37.22966666666666
+    - type: mrr_at_100
+      value: 38.066583333333334
+    - type: mrr_at_1000
+      value: 38.12616666666667
+    - type: mrr_at_3
+      value: 34.92275
+    - type: mrr_at_5
+      value: 36.23333333333334
+    - type: ndcg_at_1
+      value: 29.305666666666664
+    - type: ndcg_at_10
+      value: 38.25533333333333
+    - type: ndcg_at_100
+      value: 43.25266666666666
+    - type: ndcg_at_1000
+      value: 45.63583333333334
+    - type: ndcg_at_3
+      value: 33.777166666666666
+    - type: ndcg_at_5
+      value: 35.85
+    - type: precision_at_1
+      value: 29.305666666666664
+    - type: precision_at_10
+      value: 6.596416666666667
+    - type: precision_at_100
+      value: 1.0784166666666668
+    - type: precision_at_1000
+      value: 0.14666666666666664
+    - type: precision_at_3
+      value: 15.31075
+    - type: precision_at_5
+      value: 10.830916666666667
+    - type: recall_at_1
+      value: 25.00791666666667
+    - type: recall_at_10
+      value: 49.10933333333333
+    - type: recall_at_100
+      value: 71.09216666666667
+    - type: recall_at_1000
+      value: 87.77725000000001
+    - type: recall_at_3
+      value: 36.660916666666665
+    - type: recall_at_5
+      value: 41.94149999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.521
+    - type: map_at_10
+      value: 30.043
+    - type: map_at_100
+      value: 30.936000000000003
+    - type: map_at_1000
+      value: 31.022
+    - type: map_at_3
+      value: 27.926000000000002
+    - type: map_at_5
+      value: 29.076999999999998
+    - type: mrr_at_1
+      value: 26.227
+    - type: mrr_at_10
+      value: 32.822
+    - type: mrr_at_100
+      value: 33.61
+    - type: mrr_at_1000
+      value: 33.672000000000004
+    - type: mrr_at_3
+      value: 30.776999999999997
+    - type: mrr_at_5
+      value: 31.866
+    - type: ndcg_at_1
+      value: 26.227
+    - type: ndcg_at_10
+      value: 34.041
+    - type: ndcg_at_100
+      value: 38.394
+    - type: ndcg_at_1000
+      value: 40.732
+    - type: ndcg_at_3
+      value: 30.037999999999997
+    - type: ndcg_at_5
+      value: 31.845000000000002
+    - type: precision_at_1
+      value: 26.227
+    - type: precision_at_10
+      value: 5.244999999999999
+    - type: precision_at_100
+      value: 0.808
+    - type: precision_at_1000
+      value: 0.107
+    - type: precision_at_3
+      value: 12.679000000000002
+    - type: precision_at_5
+      value: 8.773
+    - type: recall_at_1
+      value: 23.521
+    - type: recall_at_10
+      value: 43.633
+    - type: recall_at_100
+      value: 63.126000000000005
+    - type: recall_at_1000
+      value: 80.765
+    - type: recall_at_3
+      value: 32.614
+    - type: recall_at_5
+      value: 37.15
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 16.236
+    - type: map_at_10
+      value: 22.898
+    - type: map_at_100
+      value: 23.878
+    - type: map_at_1000
+      value: 24.009
+    - type: map_at_3
+      value: 20.87
+    - type: map_at_5
+      value: 22.025
+    - type: mrr_at_1
+      value: 19.339000000000002
+    - type: mrr_at_10
+      value: 26.382
+    - type: mrr_at_100
+      value: 27.245
+    - type: mrr_at_1000
+      value: 27.33
+    - type: mrr_at_3
+      value: 24.386
+    - type: mrr_at_5
+      value: 25.496000000000002
+    - type: ndcg_at_1
+      value: 19.339000000000002
+    - type: ndcg_at_10
+      value: 27.139999999999997
+    - type: ndcg_at_100
+      value: 31.944
+    - type: ndcg_at_1000
+      value: 35.077999999999996
+    - type: ndcg_at_3
+      value: 23.424
+    - type: ndcg_at_5
+      value: 25.188
+    - type: precision_at_1
+      value: 19.339000000000002
+    - type: precision_at_10
+      value: 4.8309999999999995
+    - type: precision_at_100
+      value: 0.845
+    - type: precision_at_1000
+      value: 0.128
+    - type: precision_at_3
+      value: 10.874
+    - type: precision_at_5
+      value: 7.825
+    - type: recall_at_1
+      value: 16.236
+    - type: recall_at_10
+      value: 36.513
+    - type: recall_at_100
+      value: 57.999
+    - type: recall_at_1000
+      value: 80.512
+    - type: recall_at_3
+      value: 26.179999999999996
+    - type: recall_at_5
+      value: 30.712
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.11
+    - type: map_at_10
+      value: 31.566
+    - type: map_at_100
+      value: 32.647
+    - type: map_at_1000
+      value: 32.753
+    - type: map_at_3
+      value: 29.24
+    - type: map_at_5
+      value: 30.564999999999998
+    - type: mrr_at_1
+      value: 28.265
+    - type: mrr_at_10
+      value: 35.504000000000005
+    - type: mrr_at_100
+      value: 36.436
+    - type: mrr_at_1000
+      value: 36.503
+    - type: mrr_at_3
+      value: 33.349000000000004
+    - type: mrr_at_5
+      value: 34.622
+    - type: ndcg_at_1
+      value: 28.265
+    - type: ndcg_at_10
+      value: 36.192
+    - type: ndcg_at_100
+      value: 41.388000000000005
+    - type: ndcg_at_1000
+      value: 43.948
+    - type: ndcg_at_3
+      value: 31.959
+    - type: ndcg_at_5
+      value: 33.998
+    - type: precision_at_1
+      value: 28.265
+    - type: precision_at_10
+      value: 5.989
+    - type: precision_at_100
+      value: 0.9650000000000001
+    - type: precision_at_1000
+      value: 0.13
+    - type: precision_at_3
+      value: 14.335
+    - type: precision_at_5
+      value: 10.112
+    - type: recall_at_1
+      value: 24.11
+    - type: recall_at_10
+      value: 46.418
+    - type: recall_at_100
+      value: 69.314
+    - type: recall_at_1000
+      value: 87.397
+    - type: recall_at_3
+      value: 34.724
+    - type: recall_at_5
+      value: 39.925
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.091
+    - type: map_at_10
+      value: 29.948999999999998
+    - type: map_at_100
+      value: 31.502000000000002
+    - type: map_at_1000
+      value: 31.713
+    - type: map_at_3
+      value: 27.464
+    - type: map_at_5
+      value: 28.968
+    - type: mrr_at_1
+      value: 26.482
+    - type: mrr_at_10
+      value: 34.009
+    - type: mrr_at_100
+      value: 35.081
+    - type: mrr_at_1000
+      value: 35.138000000000005
+    - type: mrr_at_3
+      value: 31.785000000000004
+    - type: mrr_at_5
+      value: 33.178999999999995
+    - type: ndcg_at_1
+      value: 26.482
+    - type: ndcg_at_10
+      value: 35.008
+    - type: ndcg_at_100
+      value: 41.272999999999996
+    - type: ndcg_at_1000
+      value: 43.972
+    - type: ndcg_at_3
+      value: 30.804
+    - type: ndcg_at_5
+      value: 33.046
+    - type: precision_at_1
+      value: 26.482
+    - type: precision_at_10
+      value: 6.462
+    - type: precision_at_100
+      value: 1.431
+    - type: precision_at_1000
+      value: 0.22899999999999998
+    - type: precision_at_3
+      value: 14.360999999999999
+    - type: precision_at_5
+      value: 10.474
+    - type: recall_at_1
+      value: 22.091
+    - type: recall_at_10
+      value: 45.125
+    - type: recall_at_100
+      value: 72.313
+    - type: recall_at_1000
+      value: 89.503
+    - type: recall_at_3
+      value: 33.158
+    - type: recall_at_5
+      value: 39.086999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 19.883
+    - type: map_at_10
+      value: 26.951000000000004
+    - type: map_at_100
+      value: 27.927999999999997
+    - type: map_at_1000
+      value: 28.022000000000002
+    - type: map_at_3
+      value: 24.616
+    - type: map_at_5
+      value: 25.917
+    - type: mrr_at_1
+      value: 21.996
+    - type: mrr_at_10
+      value: 29.221000000000004
+    - type: mrr_at_100
+      value: 30.024
+    - type: mrr_at_1000
+      value: 30.095
+    - type: mrr_at_3
+      value: 26.833000000000002
+    - type: mrr_at_5
+      value: 28.155
+    - type: ndcg_at_1
+      value: 21.996
+    - type: ndcg_at_10
+      value: 31.421
+    - type: ndcg_at_100
+      value: 36.237
+    - type: ndcg_at_1000
+      value: 38.744
+    - type: ndcg_at_3
+      value: 26.671
+    - type: ndcg_at_5
+      value: 28.907
+    - type: precision_at_1
+      value: 21.996
+    - type: precision_at_10
+      value: 5.009
+    - type: precision_at_100
+      value: 0.799
+    - type: precision_at_1000
+      value: 0.11199999999999999
+    - type: precision_at_3
+      value: 11.275
+    - type: precision_at_5
+      value: 8.059
+    - type: recall_at_1
+      value: 19.883
+    - type: recall_at_10
+      value: 43.132999999999996
+    - type: recall_at_100
+      value: 65.654
+    - type: recall_at_1000
+      value: 84.492
+    - type: recall_at_3
+      value: 30.209000000000003
+    - type: recall_at_5
+      value: 35.616
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 17.756
+    - type: map_at_10
+      value: 30.378
+    - type: map_at_100
+      value: 32.537
+    - type: map_at_1000
+      value: 32.717
+    - type: map_at_3
+      value: 25.599
+    - type: map_at_5
+      value: 28.372999999999998
+    - type: mrr_at_1
+      value: 41.303
+    - type: mrr_at_10
+      value: 53.483999999999995
+    - type: mrr_at_100
+      value: 54.106
+    - type: mrr_at_1000
+      value: 54.127
+    - type: mrr_at_3
+      value: 50.315
+    - type: mrr_at_5
+      value: 52.396
+    - type: ndcg_at_1
+      value: 41.303
+    - type: ndcg_at_10
+      value: 40.503
+    - type: ndcg_at_100
+      value: 47.821000000000005
+    - type: ndcg_at_1000
+      value: 50.788
+    - type: ndcg_at_3
+      value: 34.364
+    - type: ndcg_at_5
+      value: 36.818
+    - type: precision_at_1
+      value: 41.303
+    - type: precision_at_10
+      value: 12.463000000000001
+    - type: precision_at_100
+      value: 2.037
+    - type: precision_at_1000
+      value: 0.26
+    - type: precision_at_3
+      value: 25.798
+    - type: precision_at_5
+      value: 19.896
+    - type: recall_at_1
+      value: 17.756
+    - type: recall_at_10
+      value: 46.102
+    - type: recall_at_100
+      value: 70.819
+    - type: recall_at_1000
+      value: 87.21799999999999
+    - type: recall_at_3
+      value: 30.646
+    - type: recall_at_5
+      value: 38.022
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 9.033
+    - type: map_at_10
+      value: 20.584
+    - type: map_at_100
+      value: 29.518
+    - type: map_at_1000
+      value: 31.186000000000003
+    - type: map_at_3
+      value: 14.468
+    - type: map_at_5
+      value: 17.177
+    - type: mrr_at_1
+      value: 69.75
+    - type: mrr_at_10
+      value: 77.025
+    - type: mrr_at_100
+      value: 77.36699999999999
+    - type: mrr_at_1000
+      value: 77.373
+    - type: mrr_at_3
+      value: 75.583
+    - type: mrr_at_5
+      value: 76.396
+    - type: ndcg_at_1
+      value: 58.5
+    - type: ndcg_at_10
+      value: 45.033
+    - type: ndcg_at_100
+      value: 49.071
+    - type: ndcg_at_1000
+      value: 56.056
+    - type: ndcg_at_3
+      value: 49.936
+    - type: ndcg_at_5
+      value: 47.471999999999994
+    - type: precision_at_1
+      value: 69.75
+    - type: precision_at_10
+      value: 35.775
+    - type: precision_at_100
+      value: 11.594999999999999
+    - type: precision_at_1000
+      value: 2.062
+    - type: precision_at_3
+      value: 52.5
+    - type: precision_at_5
+      value: 45.300000000000004
+    - type: recall_at_1
+      value: 9.033
+    - type: recall_at_10
+      value: 26.596999999999998
+    - type: recall_at_100
+      value: 54.607000000000006
+    - type: recall_at_1000
+      value: 76.961
+    - type: recall_at_3
+      value: 15.754999999999999
+    - type: recall_at_5
+      value: 20.033
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 48.345000000000006
+    - type: f1
+      value: 43.4514918068706
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 71.29100000000001
+    - type: map_at_10
+      value: 81.059
+    - type: map_at_100
+      value: 81.341
+    - type: map_at_1000
+      value: 81.355
+    - type: map_at_3
+      value: 79.74799999999999
+    - type: map_at_5
+      value: 80.612
+    - type: mrr_at_1
+      value: 76.40299999999999
+    - type: mrr_at_10
+      value: 84.615
+    - type: mrr_at_100
+      value: 84.745
+    - type: mrr_at_1000
+      value: 84.748
+    - type: mrr_at_3
+      value: 83.776
+    - type: mrr_at_5
+      value: 84.343
+    - type: ndcg_at_1
+      value: 76.40299999999999
+    - type: ndcg_at_10
+      value: 84.981
+    - type: ndcg_at_100
+      value: 86.00999999999999
+    - type: ndcg_at_1000
+      value: 86.252
+    - type: ndcg_at_3
+      value: 82.97
+    - type: ndcg_at_5
+      value: 84.152
+    - type: precision_at_1
+      value: 76.40299999999999
+    - type: precision_at_10
+      value: 10.446
+    - type: precision_at_100
+      value: 1.1199999999999999
+    - type: precision_at_1000
+      value: 0.116
+    - type: precision_at_3
+      value: 32.147999999999996
+    - type: precision_at_5
+      value: 20.135
+    - type: recall_at_1
+      value: 71.29100000000001
+    - type: recall_at_10
+      value: 93.232
+    - type: recall_at_100
+      value: 97.363
+    - type: recall_at_1000
+      value: 98.905
+    - type: recall_at_3
+      value: 87.893
+    - type: recall_at_5
+      value: 90.804
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 18.667
+    - type: map_at_10
+      value: 30.853
+    - type: map_at_100
+      value: 32.494
+    - type: map_at_1000
+      value: 32.677
+    - type: map_at_3
+      value: 26.91
+    - type: map_at_5
+      value: 29.099000000000004
+    - type: mrr_at_1
+      value: 37.191
+    - type: mrr_at_10
+      value: 46.171
+    - type: mrr_at_100
+      value: 47.056
+    - type: mrr_at_1000
+      value: 47.099000000000004
+    - type: mrr_at_3
+      value: 44.059
+    - type: mrr_at_5
+      value: 45.147
+    - type: ndcg_at_1
+      value: 37.191
+    - type: ndcg_at_10
+      value: 38.437
+    - type: ndcg_at_100
+      value: 44.62
+    - type: ndcg_at_1000
+      value: 47.795
+    - type: ndcg_at_3
+      value: 35.003
+    - type: ndcg_at_5
+      value: 36.006
+    - type: precision_at_1
+      value: 37.191
+    - type: precision_at_10
+      value: 10.586
+    - type: precision_at_100
+      value: 1.688
+    - type: precision_at_1000
+      value: 0.22699999999999998
+    - type: precision_at_3
+      value: 23.302
+    - type: precision_at_5
+      value: 17.006
+    - type: recall_at_1
+      value: 18.667
+    - type: recall_at_10
+      value: 45.367000000000004
+    - type: recall_at_100
+      value: 68.207
+    - type: recall_at_1000
+      value: 87.072
+    - type: recall_at_3
+      value: 32.129000000000005
+    - type: recall_at_5
+      value: 37.719
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 39.494
+    - type: map_at_10
+      value: 66.223
+    - type: map_at_100
+      value: 67.062
+    - type: map_at_1000
+      value: 67.11500000000001
+    - type: map_at_3
+      value: 62.867
+    - type: map_at_5
+      value: 64.994
+    - type: mrr_at_1
+      value: 78.987
+    - type: mrr_at_10
+      value: 84.585
+    - type: mrr_at_100
+      value: 84.773
+    - type: mrr_at_1000
+      value: 84.77900000000001
+    - type: mrr_at_3
+      value: 83.592
+    - type: mrr_at_5
+      value: 84.235
+    - type: ndcg_at_1
+      value: 78.987
+    - type: ndcg_at_10
+      value: 73.64
+    - type: ndcg_at_100
+      value: 76.519
+    - type: ndcg_at_1000
+      value: 77.51
+    - type: ndcg_at_3
+      value: 68.893
+    - type: ndcg_at_5
+      value: 71.585
+    - type: precision_at_1
+      value: 78.987
+    - type: precision_at_10
+      value: 15.529000000000002
+    - type: precision_at_100
+      value: 1.7770000000000001
+    - type: precision_at_1000
+      value: 0.191
+    - type: precision_at_3
+      value: 44.808
+    - type: precision_at_5
+      value: 29.006999999999998
+    - type: recall_at_1
+      value: 39.494
+    - type: recall_at_10
+      value: 77.643
+    - type: recall_at_100
+      value: 88.825
+    - type: recall_at_1000
+      value: 95.321
+    - type: recall_at_3
+      value: 67.211
+    - type: recall_at_5
+      value: 72.519
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 85.55959999999999
+    - type: ap
+      value: 80.7246500384617
+    - type: f1
+      value: 85.52336485065454
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.631
+    - type: map_at_10
+      value: 36.264
+    - type: map_at_100
+      value: 37.428
+    - type: map_at_1000
+      value: 37.472
+    - type: map_at_3
+      value: 32.537
+    - type: map_at_5
+      value: 34.746
+    - type: mrr_at_1
+      value: 24.312
+    - type: mrr_at_10
+      value: 36.858000000000004
+    - type: mrr_at_100
+      value: 37.966
+    - type: mrr_at_1000
+      value: 38.004
+    - type: mrr_at_3
+      value: 33.188
+    - type: mrr_at_5
+      value: 35.367
+    - type: ndcg_at_1
+      value: 24.312
+    - type: ndcg_at_10
+      value: 43.126999999999995
+    - type: ndcg_at_100
+      value: 48.642
+    - type: ndcg_at_1000
+      value: 49.741
+    - type: ndcg_at_3
+      value: 35.589
+    - type: ndcg_at_5
+      value: 39.515
+    - type: precision_at_1
+      value: 24.312
+    - type: precision_at_10
+      value: 6.699
+    - type: precision_at_100
+      value: 0.9450000000000001
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 15.153
+    - type: precision_at_5
+      value: 11.065999999999999
+    - type: recall_at_1
+      value: 23.631
+    - type: recall_at_10
+      value: 64.145
+    - type: recall_at_100
+      value: 89.41
+    - type: recall_at_1000
+      value: 97.83500000000001
+    - type: recall_at_3
+      value: 43.769000000000005
+    - type: recall_at_5
+      value: 53.169
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 93.4108527131783
+    - type: f1
+      value: 93.1415880261038
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 77.24806201550388
+    - type: f1
+      value: 60.531916308197175
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 73.71553463349024
+    - type: f1
+      value: 71.70753174900791
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 77.79757901815736
+    - type: f1
+      value: 77.83719850433258
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 33.74193296622113
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 30.64257594108566
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 30.811018518883625
+    - type: mrr
+      value: 31.910376577445003
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.409
+    - type: map_at_10
+      value: 13.093
+    - type: map_at_100
+      value: 16.256999999999998
+    - type: map_at_1000
+      value: 17.617
+    - type: map_at_3
+      value: 9.555
+    - type: map_at_5
+      value: 11.428
+    - type: mrr_at_1
+      value: 45.201
+    - type: mrr_at_10
+      value: 54.179
+    - type: mrr_at_100
+      value: 54.812000000000005
+    - type: mrr_at_1000
+      value: 54.840999999999994
+    - type: mrr_at_3
+      value: 51.909000000000006
+    - type: mrr_at_5
+      value: 53.519000000000005
+    - type: ndcg_at_1
+      value: 43.189
+    - type: ndcg_at_10
+      value: 35.028
+    - type: ndcg_at_100
+      value: 31.226
+    - type: ndcg_at_1000
+      value: 39.678000000000004
+    - type: ndcg_at_3
+      value: 40.596
+    - type: ndcg_at_5
+      value: 38.75
+    - type: precision_at_1
+      value: 44.582
+    - type: precision_at_10
+      value: 25.974999999999998
+    - type: precision_at_100
+      value: 7.793
+    - type: precision_at_1000
+      value: 2.036
+    - type: precision_at_3
+      value: 38.493
+    - type: precision_at_5
+      value: 33.994
+    - type: recall_at_1
+      value: 5.409
+    - type: recall_at_10
+      value: 16.875999999999998
+    - type: recall_at_100
+      value: 30.316
+    - type: recall_at_1000
+      value: 60.891
+    - type: recall_at_3
+      value: 10.688
+    - type: recall_at_5
+      value: 13.832
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 36.375
+    - type: map_at_10
+      value: 51.991
+    - type: map_at_100
+      value: 52.91400000000001
+    - type: map_at_1000
+      value: 52.93600000000001
+    - type: map_at_3
+      value: 48.014
+    - type: map_at_5
+      value: 50.381
+    - type: mrr_at_1
+      value: 40.759
+    - type: mrr_at_10
+      value: 54.617000000000004
+    - type: mrr_at_100
+      value: 55.301
+    - type: mrr_at_1000
+      value: 55.315000000000005
+    - type: mrr_at_3
+      value: 51.516
+    - type: mrr_at_5
+      value: 53.435
+    - type: ndcg_at_1
+      value: 40.759
+    - type: ndcg_at_10
+      value: 59.384
+    - type: ndcg_at_100
+      value: 63.157
+    - type: ndcg_at_1000
+      value: 63.654999999999994
+    - type: ndcg_at_3
+      value: 52.114000000000004
+    - type: ndcg_at_5
+      value: 55.986000000000004
+    - type: precision_at_1
+      value: 40.759
+    - type: precision_at_10
+      value: 9.411999999999999
+    - type: precision_at_100
+      value: 1.153
+    - type: precision_at_1000
+      value: 0.12
+    - type: precision_at_3
+      value: 23.329
+    - type: precision_at_5
+      value: 16.256999999999998
+    - type: recall_at_1
+      value: 36.375
+    - type: recall_at_10
+      value: 79.053
+    - type: recall_at_100
+      value: 95.167
+    - type: recall_at_1000
+      value: 98.82
+    - type: recall_at_3
+      value: 60.475
+    - type: recall_at_5
+      value: 69.327
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 70.256
+    - type: map_at_10
+      value: 83.8
+    - type: map_at_100
+      value: 84.425
+    - type: map_at_1000
+      value: 84.444
+    - type: map_at_3
+      value: 80.906
+    - type: map_at_5
+      value: 82.717
+    - type: mrr_at_1
+      value: 80.97999999999999
+    - type: mrr_at_10
+      value: 87.161
+    - type: mrr_at_100
+      value: 87.262
+    - type: mrr_at_1000
+      value: 87.263
+    - type: mrr_at_3
+      value: 86.175
+    - type: mrr_at_5
+      value: 86.848
+    - type: ndcg_at_1
+      value: 80.97999999999999
+    - type: ndcg_at_10
+      value: 87.697
+    - type: ndcg_at_100
+      value: 88.959
+    - type: ndcg_at_1000
+      value: 89.09899999999999
+    - type: ndcg_at_3
+      value: 84.83800000000001
+    - type: ndcg_at_5
+      value: 86.401
+    - type: precision_at_1
+      value: 80.97999999999999
+    - type: precision_at_10
+      value: 13.261000000000001
+    - type: precision_at_100
+      value: 1.5150000000000001
+    - type: precision_at_1000
+      value: 0.156
+    - type: precision_at_3
+      value: 37.01
+    - type: precision_at_5
+      value: 24.298000000000002
+    - type: recall_at_1
+      value: 70.256
+    - type: recall_at_10
+      value: 94.935
+    - type: recall_at_100
+      value: 99.274
+    - type: recall_at_1000
+      value: 99.928
+    - type: recall_at_3
+      value: 86.602
+    - type: recall_at_5
+      value: 91.133
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 56.322692497613104
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 61.895813503775074
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 4.338
+    - type: map_at_10
+      value: 10.767
+    - type: map_at_100
+      value: 12.537999999999998
+    - type: map_at_1000
+      value: 12.803999999999998
+    - type: map_at_3
+      value: 7.788
+    - type: map_at_5
+      value: 9.302000000000001
+    - type: mrr_at_1
+      value: 21.4
+    - type: mrr_at_10
+      value: 31.637999999999998
+    - type: mrr_at_100
+      value: 32.688
+    - type: mrr_at_1000
+      value: 32.756
+    - type: mrr_at_3
+      value: 28.433000000000003
+    - type: mrr_at_5
+      value: 30.178
+    - type: ndcg_at_1
+      value: 21.4
+    - type: ndcg_at_10
+      value: 18.293
+    - type: ndcg_at_100
+      value: 25.274
+    - type: ndcg_at_1000
+      value: 30.284
+    - type: ndcg_at_3
+      value: 17.391000000000002
+    - type: ndcg_at_5
+      value: 15.146999999999998
+    - type: precision_at_1
+      value: 21.4
+    - type: precision_at_10
+      value: 9.48
+    - type: precision_at_100
+      value: 1.949
+    - type: precision_at_1000
+      value: 0.316
+    - type: precision_at_3
+      value: 16.167
+    - type: precision_at_5
+      value: 13.22
+    - type: recall_at_1
+      value: 4.338
+    - type: recall_at_10
+      value: 19.213
+    - type: recall_at_100
+      value: 39.562999999999995
+    - type: recall_at_1000
+      value: 64.08
+    - type: recall_at_3
+      value: 9.828000000000001
+    - type: recall_at_5
+      value: 13.383000000000001
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.42568163642142
+    - type: cos_sim_spearman
+      value: 78.5797159641342
+    - type: euclidean_pearson
+      value: 80.22151260811604
+    - type: euclidean_spearman
+      value: 78.5797151953878
+    - type: manhattan_pearson
+      value: 80.21224215864788
+    - type: manhattan_spearman
+      value: 78.55641478381344
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 85.44020710812569
+    - type: cos_sim_spearman
+      value: 78.91631735081286
+    - type: euclidean_pearson
+      value: 81.64188964182102
+    - type: euclidean_spearman
+      value: 78.91633286881678
+    - type: manhattan_pearson
+      value: 81.69294748512496
+    - type: manhattan_spearman
+      value: 78.93438558002656
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.27165426412311
+    - type: cos_sim_spearman
+      value: 85.40429140249618
+    - type: euclidean_pearson
+      value: 84.7509580724893
+    - type: euclidean_spearman
+      value: 85.40429140249618
+    - type: manhattan_pearson
+      value: 84.76488289321308
+    - type: manhattan_spearman
+      value: 85.4256793698708
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.138851760732
+    - type: cos_sim_spearman
+      value: 81.64101363896586
+    - type: euclidean_pearson
+      value: 82.55165038934942
+    - type: euclidean_spearman
+      value: 81.64105257080502
+    - type: manhattan_pearson
+      value: 82.52802949883335
+    - type: manhattan_spearman
+      value: 81.61255430718158
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.0654695484029
+    - type: cos_sim_spearman
+      value: 87.20408521902229
+    - type: euclidean_pearson
+      value: 86.8110651362115
+    - type: euclidean_spearman
+      value: 87.20408521902229
+    - type: manhattan_pearson
+      value: 86.77984656478691
+    - type: manhattan_spearman
+      value: 87.1719947099227
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.77823915496512
+    - type: cos_sim_spearman
+      value: 85.43566325729779
+    - type: euclidean_pearson
+      value: 84.5396956658821
+    - type: euclidean_spearman
+      value: 85.43566325729779
+    - type: manhattan_pearson
+      value: 84.5665398848169
+    - type: manhattan_spearman
+      value: 85.44375870303232
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts17-crosslingual-sts
+      name: MTEB STS17 (en-en)
+      config: en-en
+      split: test
+      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.20030208471798
+    - type: cos_sim_spearman
+      value: 87.20485505076539
+    - type: euclidean_pearson
+      value: 88.10588324368722
+    - type: euclidean_spearman
+      value: 87.20485505076539
+    - type: manhattan_pearson
+      value: 87.92324770415183
+    - type: manhattan_spearman
+      value: 87.0571314561877
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts22-crosslingual-sts
+      name: MTEB STS22 (en)
+      config: en
+      split: test
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+    metrics:
+    - type: cos_sim_pearson
+      value: 63.06093161604453
+    - type: cos_sim_spearman
+      value: 64.2163140357722
+    - type: euclidean_pearson
+      value: 65.27589680994006
+    - type: euclidean_spearman
+      value: 64.2163140357722
+    - type: manhattan_pearson
+      value: 65.45904383711101
+    - type: manhattan_spearman
+      value: 64.55404716679305
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.32976164578706
+    - type: cos_sim_spearman
+      value: 85.54302197678368
+    - type: euclidean_pearson
+      value: 85.26307149193056
+    - type: euclidean_spearman
+      value: 85.54302197678368
+    - type: manhattan_pearson
+      value: 85.26647282029371
+    - type: manhattan_spearman
+      value: 85.5316135265568
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 81.44675968318754
+    - type: mrr
+      value: 94.92741826075158
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 56.34400000000001
+    - type: map_at_10
+      value: 65.927
+    - type: map_at_100
+      value: 66.431
+    - type: map_at_1000
+      value: 66.461
+    - type: map_at_3
+      value: 63.529
+    - type: map_at_5
+      value: 64.818
+    - type: mrr_at_1
+      value: 59.333000000000006
+    - type: mrr_at_10
+      value: 67.54599999999999
+    - type: mrr_at_100
+      value: 67.892
+    - type: mrr_at_1000
+      value: 67.917
+    - type: mrr_at_3
+      value: 65.778
+    - type: mrr_at_5
+      value: 66.794
+    - type: ndcg_at_1
+      value: 59.333000000000006
+    - type: ndcg_at_10
+      value: 70.5
+    - type: ndcg_at_100
+      value: 72.688
+    - type: ndcg_at_1000
+      value: 73.483
+    - type: ndcg_at_3
+      value: 66.338
+    - type: ndcg_at_5
+      value: 68.265
+    - type: precision_at_1
+      value: 59.333000000000006
+    - type: precision_at_10
+      value: 9.3
+    - type: precision_at_100
+      value: 1.053
+    - type: precision_at_1000
+      value: 0.11199999999999999
+    - type: precision_at_3
+      value: 25.889
+    - type: precision_at_5
+      value: 16.866999999999997
+    - type: recall_at_1
+      value: 56.34400000000001
+    - type: recall_at_10
+      value: 82.789
+    - type: recall_at_100
+      value: 92.767
+    - type: recall_at_1000
+      value: 99
+    - type: recall_at_3
+      value: 71.64399999999999
+    - type: recall_at_5
+      value: 76.322
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.75742574257426
+    - type: cos_sim_ap
+      value: 93.52081548447406
+    - type: cos_sim_f1
+      value: 87.33850129198966
+    - type: cos_sim_precision
+      value: 90.37433155080214
+    - type: cos_sim_recall
+      value: 84.5
+    - type: dot_accuracy
+      value: 99.75742574257426
+    - type: dot_ap
+      value: 93.52081548447406
+    - type: dot_f1
+      value: 87.33850129198966
+    - type: dot_precision
+      value: 90.37433155080214
+    - type: dot_recall
+      value: 84.5
+    - type: euclidean_accuracy
+      value: 99.75742574257426
+    - type: euclidean_ap
+      value: 93.52081548447406
+    - type: euclidean_f1
+      value: 87.33850129198966
+    - type: euclidean_precision
+      value: 90.37433155080214
+    - type: euclidean_recall
+      value: 84.5
+    - type: manhattan_accuracy
+      value: 99.75841584158415
+    - type: manhattan_ap
+      value: 93.4975678585854
+    - type: manhattan_f1
+      value: 87.26708074534162
+    - type: manhattan_precision
+      value: 90.45064377682404
+    - type: manhattan_recall
+      value: 84.3
+    - type: max_accuracy
+      value: 99.75841584158415
+    - type: max_ap
+      value: 93.52081548447406
+    - type: max_f1
+      value: 87.33850129198966
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 64.31437036686651
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 33.25569319007206
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 49.90474939720706
+    - type: mrr
+      value: 50.568115503777264
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 29.866828641244712
+    - type: cos_sim_spearman
+      value: 30.077555055873866
+    - type: dot_pearson
+      value: 29.866832988572266
+    - type: dot_spearman
+      value: 30.077555055873866
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.232
+    - type: map_at_10
+      value: 2.094
+    - type: map_at_100
+      value: 11.971
+    - type: map_at_1000
+      value: 28.158
+    - type: map_at_3
+      value: 0.688
+    - type: map_at_5
+      value: 1.114
+    - 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: 84
+    - type: ndcg_at_10
+      value: 79.923
+    - type: ndcg_at_100
+      value: 61.17
+    - type: ndcg_at_1000
+      value: 53.03
+    - type: ndcg_at_3
+      value: 84.592
+    - type: ndcg_at_5
+      value: 82.821
+    - type: precision_at_1
+      value: 88
+    - type: precision_at_10
+      value: 85
+    - type: precision_at_100
+      value: 63.019999999999996
+    - type: precision_at_1000
+      value: 23.554
+    - type: precision_at_3
+      value: 89.333
+    - type: precision_at_5
+      value: 87.2
+    - type: recall_at_1
+      value: 0.232
+    - type: recall_at_10
+      value: 2.255
+    - type: recall_at_100
+      value: 14.823
+    - type: recall_at_1000
+      value: 49.456
+    - type: recall_at_3
+      value: 0.718
+    - type: recall_at_5
+      value: 1.175
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 2.547
+    - type: map_at_10
+      value: 11.375
+    - type: map_at_100
+      value: 18.194
+    - type: map_at_1000
+      value: 19.749
+    - type: map_at_3
+      value: 5.825
+    - type: map_at_5
+      value: 8.581
+    - type: mrr_at_1
+      value: 32.653
+    - type: mrr_at_10
+      value: 51.32
+    - type: mrr_at_100
+      value: 51.747
+    - type: mrr_at_1000
+      value: 51.747
+    - type: mrr_at_3
+      value: 47.278999999999996
+    - type: mrr_at_5
+      value: 48.605
+    - type: ndcg_at_1
+      value: 29.592000000000002
+    - type: ndcg_at_10
+      value: 28.151
+    - type: ndcg_at_100
+      value: 39.438
+    - type: ndcg_at_1000
+      value: 50.769
+    - type: ndcg_at_3
+      value: 30.758999999999997
+    - type: ndcg_at_5
+      value: 30.366
+    - type: precision_at_1
+      value: 32.653
+    - type: precision_at_10
+      value: 25.714
+    - type: precision_at_100
+      value: 8.041
+    - type: precision_at_1000
+      value: 1.555
+    - type: precision_at_3
+      value: 33.333
+    - type: precision_at_5
+      value: 31.837
+    - type: recall_at_1
+      value: 2.547
+    - type: recall_at_10
+      value: 18.19
+    - type: recall_at_100
+      value: 49.538
+    - type: recall_at_1000
+      value: 83.86
+    - type: recall_at_3
+      value: 7.329
+    - type: recall_at_5
+      value: 11.532
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 71.4952
+    - type: ap
+      value: 14.793362635531409
+    - type: f1
+      value: 55.204635551516915
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 61.5365025466893
+    - type: f1
+      value: 61.81742556334845
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 49.05531070301185
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 86.51725576682364
+    - type: cos_sim_ap
+      value: 75.2292304265163
+    - type: cos_sim_f1
+      value: 69.54022988505749
+    - type: cos_sim_precision
+      value: 63.65629110039457
+    - type: cos_sim_recall
+      value: 76.62269129287598
+    - type: dot_accuracy
+      value: 86.51725576682364
+    - type: dot_ap
+      value: 75.22922386081054
+    - type: dot_f1
+      value: 69.54022988505749
+    - type: dot_precision
+      value: 63.65629110039457
+    - type: dot_recall
+      value: 76.62269129287598
+    - type: euclidean_accuracy
+      value: 86.51725576682364
+    - type: euclidean_ap
+      value: 75.22925730473472
+    - type: euclidean_f1
+      value: 69.54022988505749
+    - type: euclidean_precision
+      value: 63.65629110039457
+    - type: euclidean_recall
+      value: 76.62269129287598
+    - type: manhattan_accuracy
+      value: 86.52321630804077
+    - type: manhattan_ap
+      value: 75.20608115037336
+    - type: manhattan_f1
+      value: 69.60000000000001
+    - type: manhattan_precision
+      value: 64.37219730941705
+    - type: manhattan_recall
+      value: 75.75197889182058
+    - type: max_accuracy
+      value: 86.52321630804077
+    - type: max_ap
+      value: 75.22925730473472
+    - type: max_f1
+      value: 69.60000000000001
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 89.34877944657896
+    - type: cos_sim_ap
+      value: 86.71257569277373
+    - type: cos_sim_f1
+      value: 79.10386355986088
+    - type: cos_sim_precision
+      value: 76.91468470434214
+    - type: cos_sim_recall
+      value: 81.4213119802895
+    - type: dot_accuracy
+      value: 89.34877944657896
+    - type: dot_ap
+      value: 86.71257133133368
+    - type: dot_f1
+      value: 79.10386355986088
+    - type: dot_precision
+      value: 76.91468470434214
+    - type: dot_recall
+      value: 81.4213119802895
+    - type: euclidean_accuracy
+      value: 89.34877944657896
+    - type: euclidean_ap
+      value: 86.71257651501476
+    - type: euclidean_f1
+      value: 79.10386355986088
+    - type: euclidean_precision
+      value: 76.91468470434214
+    - type: euclidean_recall
+      value: 81.4213119802895
+    - type: manhattan_accuracy
+      value: 89.35848177901967
+    - type: manhattan_ap
+      value: 86.69330615469126
+    - type: manhattan_f1
+      value: 79.13867741453949
+    - type: manhattan_precision
+      value: 76.78881807647741
+    - type: manhattan_recall
+      value: 81.63689559593472
+    - type: max_accuracy
+      value: 89.35848177901967
+    - type: max_ap
+      value: 86.71257651501476
+    - type: max_f1
+      value: 79.13867741453949
 license: apache-2.0
+language:
+- en
 ---
+
+
+# nomic-embed-text-v1: A Reproducible Long Context (8192) Text Embedder 
+
+`nomic-embed-text-v1` is 8192 context length text encoder that surpasses OpenAI text-embedding-ada-002 and text-embedding-3-small performance on short and long context tasks.
+
+
+
+| Name                             | SeqLen | MTEB      | LoCo     | Jina Long Context |  Open Weights | Open Training Code | Open Data   |
+| :-------------------------------:| :----- | :-------- | :------: | :---------------: | :-----------: | :----------------: | :---------- |
+| nomic-embed-text-v1              | 8192   | **62.39** |**85.53** | 54.16             | ✅            | ✅                  | ✅          |
+| jina-embeddings-v2-base-en       | 8192   | 60.39     | 85.45    | 51.90             | ✅            | ❌                  | ❌          |
+| text-embedding-3-small           | 8191   | 62.26     | 82.40    | **58.20**         | ❌            | ❌                  | ❌          |
+| text-embedding-ada-002           | 8191   | 60.99     | 52.7     | 55.25             | ❌            | ❌                  | ❌          |
+
+
+## Hosted Inference API
+
+The easiest way to get started with Nomic Embed is through the Nomic Embedding API.
+
+Generating embeddings with the `nomic` Python client is as easy as 
+
+```python
+from nomic import embed
+
+output = embed.text(
+    texts=['Nomic Embedding API', '#keepAIOpen'],
+    model='nomic-embed-text-v1',
+    task_type='search_document'
+)
+
+print(output)
+```
+
+For more information, see the [API reference](https://docs.nomic.ai/reference/endpoints/nomic-embed-text)
+
+## Data Visualization
+Click the Nomic Atlas map below to visualize a 5M sample of our contrastive pretraining data!
+
+
+[![image/webp](https://cdn-uploads.huggingface.co/production/uploads/607997c83a565c15675055b3/pjhJhuNyRfPagRd_c_iUz.webp)](https://atlas.nomic.ai/map/nomic-text-embed-v1-5m-sample)
+
+## Training Details
+
+We train our embedder using a multi-stage training pipeline. Starting from a long-context [BERT model](https://huggingface.co/nomic-ai/nomic-bert-2048),
+the first unsupervised contrastive stage trains on a dataset generated from weakly related text pairs, such as question-answer pairs from forums like StackExchange and Quora, title-body pairs from Amazon reviews, and summarizations from news articles.
+
+In the second finetuning stage, higher quality labeled datasets such as search queries and answers from web searches are leveraged. Data curation and hard-example mining is crucial in this stage.
+
+For more details, see the Nomic Embed [Technical Report](https://static.nomic.ai/reports/2024_Nomic_Embed_Text_Technical_Report.pdf) and corresponding [blog post](https://blog.nomic.ai/posts/nomic-embed-text-v1).
+
+Training data to train the models is released in its entirety. For more details, see the `contrastors` [repository](https://github.com/nomic-ai/contrastors)
+
+## Usage
+
+Note `nomic-embed-text` requires prefixes! We support the prefixes `[search_query, search_document, classification, clustering]`.
+For retrieval applications, you should prepend `search_document` for all your documents and `search_query` for your queries.
+
+### Sentence Transformers
+```python
+from sentence_transformers import SentenceTransformer
+
+model = SentenceTransformer("nomic-ai/nomic-embed-text-v1", trust_remote_code=True)
+sentences = ['search_query: What is TSNE?', 'search_query: Who is Laurens van der Maaten?']
+embeddings = model.encode(sentences)
+print(embeddings)
+```
+
+### Transformers
+
+```python
+import torch
+import torch.nn.functional as F
+from transformers import AutoTokenizer, AutoModel
+
+def mean_pooling(model_output, attention_mask):
+    token_embeddings = model_output[0]
+    input_mask_expanded = attention_mask.unsqueeze(-1).expand(token_embeddings.size()).float()
+    return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9)
+
+sentences = ['search_query: What is TSNE?', 'search_query: Who is Laurens van der Maaten?']
+
+tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
+model = AutoModel.from_pretrained('nomic-ai/nomic-embed-text-v1', trust_remote_code=True)
+model.eval()
+
+encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')
+
+with torch.no_grad():
+    model_output = model(**encoded_input)
+
+embeddings = mean_pooling(model_output, encoded_input['attention_mask'])
+embeddings = F.normalize(embeddings, p=2, dim=1)
+print(embeddings)
+```
+
+The model natively supports scaling of the sequence length past 2048 tokens. To do so, 
+
+```diff
+- tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
++ tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased', model_max_length=8192)
+
+
+- model = AutoModel.from_pretrained('nomic-ai/nomic-embed-text-v1', trust_remote_code=True)
++ model = AutoModel.from_pretrained('nomic-ai/nomic-embed-text-v1', trust_remote_code=True, rotary_scaling_factor=2)
+```
+
+### Transformers.js
+
+```js
+import { pipeline } from '@xenova/transformers';
+
+// Create a feature extraction pipeline
+const extractor = await pipeline('feature-extraction', 'nomic-ai/nomic-embed-text-v1', {
+    quantized: false, // Comment out this line to use the quantized version
+});
+
+// Compute sentence embeddings
+const texts = ['What is TSNE?', 'Who is Laurens van der Maaten?'];
+const embeddings = await extractor(texts, { pooling: 'mean', normalize: true });
+console.log(embeddings);
+```
+
+# Join the Nomic Community
+
+- Nomic: [https://nomic.ai](https://nomic.ai)
+- Discord: [https://discord.gg/myY5YDR8z8](https://discord.gg/myY5YDR8z8)
+- Twitter: [https://twitter.com/nomic_ai](https://twitter.com/nomic_ai)
+
+
+# Citation
+
+If you find the model, dataset, or training code useful, please cite our work
+
+```bibtex
+@misc{nussbaum2024nomic,
+      title={Nomic Embed: Training a Reproducible Long Context Text Embedder}, 
+      author={Zach Nussbaum and John X. Morris and Brandon Duderstadt and Andriy Mulyar},
+      year={2024},
+      eprint={2402.01613},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```

config.json

@@ -0,0 +1,56 @@
+{
+  "activation_function": "swiglu",
+  "architectures": [
+    "NomicBertModel"
+  ],
+  "attn_pdrop": 0.0,
+  "auto_map": {
+    "AutoConfig": "configuration_hf_nomic_bert.NomicBertConfig",
+    "AutoModel": "modeling_hf_nomic_bert.NomicBertModel",
+    "AutoModelForMaskedLM": "nomic-ai/nomic-bert-2048--modeling_hf_nomic_bert.NomicBertForPreTraining"
+  },
+  "bos_token_id": null,
+  "causal": false,
+  "dense_seq_output": true,
+  "embd_pdrop": 0.0,
+  "eos_token_id": null,
+  "fused_bias_fc": true,
+  "fused_dropout_add_ln": true,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-12,
+  "mlp_fc1_bias": false,
+  "mlp_fc2_bias": false,
+  "model_type": "nomic_bert",
+  "n_embd": 768,
+  "n_head": 12,
+  "n_inner": 3072,
+  "n_layer": 12,
+  "n_positions": 8192,
+  "pad_vocab_size_multiple": 64,
+  "parallel_block": false,
+  "parallel_block_tied_norm": false,
+  "prenorm": false,
+  "qkv_proj_bias": false,
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.0,
+  "rotary_emb_base": 1000,
+  "rotary_emb_fraction": 1.0,
+  "rotary_emb_interleaved": false,
+  "rotary_emb_scale_base": null,
+  "rotary_scaling_factor": 2,
+  "scale_attn_by_inverse_layer_idx": false,
+  "scale_attn_weights": true,
+  "summary_activation": null,
+  "summary_first_dropout": 0.0,
+  "summary_proj_to_labels": true,
+  "summary_type": "cls_index",
+  "summary_use_proj": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.34.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "use_flash_attn": true,
+  "use_rms_norm": false,
+  "use_xentropy": true,
+  "vocab_size": 30528
+}

config_sentence_transformers.json

@@ -0,0 +1,7 @@
+{
+  "__version__": {
+    "sentence_transformers": "2.4.0.dev0",
+    "transformers": "4.37.2",
+    "pytorch": "2.1.0+cu121"
+  }
+}

configuration_hf_nomic_bert.py

@@ -0,0 +1,53 @@
+from transformers import GPT2Config
+
+
+class NomicBertConfig(GPT2Config):
+    model_type = "nomic_bert"
+
+    def __init__(self,
+        prenorm=False,
+        parallel_block=False,
+        parallel_block_tied_norm=False,
+        rotary_emb_fraction=0.0,
+        fused_dropout_add_ln=False,
+        fused_bias_fc=False,
+        use_flash_attn=False,
+        use_xentropy=False,
+        qkv_proj_bias=True,
+        rotary_emb_base=1000,
+        rotary_emb_scale_base=None,
+        rotary_emb_interleaved=False,
+        mlp_fc1_bias=True,
+        mlp_fc2_bias=True,
+        use_rms_norm=False,
+        causal=False,
+        type_vocab_size=2,
+        dense_seq_output=True,
+        pad_vocab_size_multiple=1,
+        tie_word_embeddings=True,
+        rotary_scaling_factor=1.0,
+        **kwargs,
+    ):
+        self.prenorm = prenorm
+        self.parallel_block = parallel_block
+        self.parallel_block_tied_norm = parallel_block_tied_norm
+        self.rotary_emb_fraction = rotary_emb_fraction
+        self.tie_word_embeddings = tie_word_embeddings
+        self.fused_dropout_add_ln = fused_dropout_add_ln
+        self.fused_bias_fc = fused_bias_fc
+        self.use_flash_attn = use_flash_attn
+        self.use_xentropy = use_xentropy
+        self.qkv_proj_bias = qkv_proj_bias
+        self.rotary_emb_base = rotary_emb_base
+        self.rotary_emb_scale_base = rotary_emb_scale_base
+        self.rotary_emb_interleaved = rotary_emb_interleaved
+        self.mlp_fc1_bias = mlp_fc1_bias
+        self.mlp_fc2_bias = mlp_fc2_bias
+        self.use_rms_norm = use_rms_norm
+        self.causal = causal
+        self.type_vocab_size = type_vocab_size
+        self.dense_seq_output = dense_seq_output
+        self.pad_vocab_size_multiple = pad_vocab_size_multiple
+        self.rotary_scaling_factor = rotary_scaling_factor
+
+        super().__init__(**kwargs)