Upload intfloat/e5-small ctranslate fp16 weights

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README.md

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+---
+tags:
+- ctranslate2
+- int8
+- float16
+- mteb
+model-index:
+- name: e5-small
+  results:
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_counterfactual
+      name: MTEB AmazonCounterfactualClassification (en)
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 76.22388059701493
+    - type: ap
+      value: 40.27466219523129
+    - type: f1
+      value: 70.60533006025108
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_polarity
+      name: MTEB AmazonPolarityClassification
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 87.525775
+    - type: ap
+      value: 83.51063993897611
+    - type: f1
+      value: 87.49342736805572
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_reviews_multi
+      name: MTEB AmazonReviewsClassification (en)
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 42.611999999999995
+    - type: f1
+      value: 42.05088045932892
+  - task:
+      type: Retrieval
+    dataset:
+      type: arguana
+      name: MTEB ArguAna
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.826
+    - type: map_at_10
+      value: 38.269
+    - type: map_at_100
+      value: 39.322
+    - type: map_at_1000
+      value: 39.344
+    - type: map_at_3
+      value: 33.428000000000004
+    - type: map_at_5
+      value: 36.063
+    - type: mrr_at_1
+      value: 24.253
+    - type: mrr_at_10
+      value: 38.425
+    - type: mrr_at_100
+      value: 39.478
+    - type: mrr_at_1000
+      value: 39.5
+    - type: mrr_at_3
+      value: 33.606
+    - type: mrr_at_5
+      value: 36.195
+    - type: ndcg_at_1
+      value: 23.826
+    - type: ndcg_at_10
+      value: 46.693
+    - type: ndcg_at_100
+      value: 51.469
+    - type: ndcg_at_1000
+      value: 52.002
+    - type: ndcg_at_3
+      value: 36.603
+    - type: ndcg_at_5
+      value: 41.365
+    - type: precision_at_1
+      value: 23.826
+    - type: precision_at_10
+      value: 7.383000000000001
+    - type: precision_at_100
+      value: 0.9530000000000001
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_3
+      value: 15.268
+    - type: precision_at_5
+      value: 11.479000000000001
+    - type: recall_at_1
+      value: 23.826
+    - type: recall_at_10
+      value: 73.82600000000001
+    - type: recall_at_100
+      value: 95.306
+    - type: recall_at_1000
+      value: 99.431
+    - type: recall_at_3
+      value: 45.804
+    - type: recall_at_5
+      value: 57.397
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-p2p
+      name: MTEB ArxivClusteringP2P
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 44.13995374767436
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/arxiv-clustering-s2s
+      name: MTEB ArxivClusteringS2S
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 37.13950072624313
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/askubuntudupquestions-reranking
+      name: MTEB AskUbuntuDupQuestions
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 59.35843292105327
+    - type: mrr
+      value: 73.72312359846987
+  - task:
+      type: STS
+    dataset:
+      type: mteb/biosses-sts
+      name: MTEB BIOSSES
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.55140418324174
+    - type: cos_sim_spearman
+      value: 84.21637675860022
+    - type: euclidean_pearson
+      value: 81.26069614610006
+    - type: euclidean_spearman
+      value: 83.25069210421785
+    - type: manhattan_pearson
+      value: 80.17441422581014
+    - type: manhattan_spearman
+      value: 81.87596198487877
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/banking77
+      name: MTEB Banking77Classification
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 81.87337662337661
+    - type: f1
+      value: 81.76647866926402
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-p2p
+      name: MTEB BiorxivClusteringP2P
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 35.80600542614507
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/biorxiv-clustering-s2s
+      name: MTEB BiorxivClusteringS2S
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 31.86321613256603
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackAndroidRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 32.054
+    - type: map_at_10
+      value: 40.699999999999996
+    - type: map_at_100
+      value: 41.818
+    - type: map_at_1000
+      value: 41.959999999999994
+    - type: map_at_3
+      value: 37.742
+    - type: map_at_5
+      value: 39.427
+    - type: mrr_at_1
+      value: 38.769999999999996
+    - type: mrr_at_10
+      value: 46.150000000000006
+    - type: mrr_at_100
+      value: 46.865
+    - type: mrr_at_1000
+      value: 46.925
+    - type: mrr_at_3
+      value: 43.705
+    - type: mrr_at_5
+      value: 45.214999999999996
+    - type: ndcg_at_1
+      value: 38.769999999999996
+    - type: ndcg_at_10
+      value: 45.778
+    - type: ndcg_at_100
+      value: 50.38
+    - type: ndcg_at_1000
+      value: 52.922999999999995
+    - type: ndcg_at_3
+      value: 41.597
+    - type: ndcg_at_5
+      value: 43.631
+    - type: precision_at_1
+      value: 38.769999999999996
+    - type: precision_at_10
+      value: 8.269
+    - type: precision_at_100
+      value: 1.278
+    - type: precision_at_1000
+      value: 0.178
+    - type: precision_at_3
+      value: 19.266
+    - type: precision_at_5
+      value: 13.705
+    - type: recall_at_1
+      value: 32.054
+    - type: recall_at_10
+      value: 54.947
+    - type: recall_at_100
+      value: 74.79599999999999
+    - type: recall_at_1000
+      value: 91.40899999999999
+    - type: recall_at_3
+      value: 42.431000000000004
+    - type: recall_at_5
+      value: 48.519
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackEnglishRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 29.035
+    - type: map_at_10
+      value: 38.007000000000005
+    - type: map_at_100
+      value: 39.125
+    - type: map_at_1000
+      value: 39.251999999999995
+    - type: map_at_3
+      value: 35.77
+    - type: map_at_5
+      value: 37.057
+    - type: mrr_at_1
+      value: 36.497
+    - type: mrr_at_10
+      value: 44.077
+    - type: mrr_at_100
+      value: 44.743
+    - type: mrr_at_1000
+      value: 44.79
+    - type: mrr_at_3
+      value: 42.123
+    - type: mrr_at_5
+      value: 43.308
+    - type: ndcg_at_1
+      value: 36.497
+    - type: ndcg_at_10
+      value: 42.986000000000004
+    - type: ndcg_at_100
+      value: 47.323
+    - type: ndcg_at_1000
+      value: 49.624
+    - type: ndcg_at_3
+      value: 39.805
+    - type: ndcg_at_5
+      value: 41.286
+    - type: precision_at_1
+      value: 36.497
+    - type: precision_at_10
+      value: 7.8340000000000005
+    - type: precision_at_100
+      value: 1.269
+    - type: precision_at_1000
+      value: 0.178
+    - type: precision_at_3
+      value: 19.023
+    - type: precision_at_5
+      value: 13.248
+    - type: recall_at_1
+      value: 29.035
+    - type: recall_at_10
+      value: 51.06
+    - type: recall_at_100
+      value: 69.64099999999999
+    - type: recall_at_1000
+      value: 84.49
+    - type: recall_at_3
+      value: 41.333999999999996
+    - type: recall_at_5
+      value: 45.663
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGamingRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 37.239
+    - type: map_at_10
+      value: 47.873
+    - type: map_at_100
+      value: 48.842999999999996
+    - type: map_at_1000
+      value: 48.913000000000004
+    - type: map_at_3
+      value: 45.050000000000004
+    - type: map_at_5
+      value: 46.498
+    - type: mrr_at_1
+      value: 42.508
+    - type: mrr_at_10
+      value: 51.44
+    - type: mrr_at_100
+      value: 52.087
+    - type: mrr_at_1000
+      value: 52.129999999999995
+    - type: mrr_at_3
+      value: 49.164
+    - type: mrr_at_5
+      value: 50.343
+    - type: ndcg_at_1
+      value: 42.508
+    - type: ndcg_at_10
+      value: 53.31399999999999
+    - type: ndcg_at_100
+      value: 57.245000000000005
+    - type: ndcg_at_1000
+      value: 58.794000000000004
+    - type: ndcg_at_3
+      value: 48.295
+    - type: ndcg_at_5
+      value: 50.415
+    - type: precision_at_1
+      value: 42.508
+    - type: precision_at_10
+      value: 8.458
+    - type: precision_at_100
+      value: 1.133
+    - type: precision_at_1000
+      value: 0.132
+    - type: precision_at_3
+      value: 21.191
+    - type: precision_at_5
+      value: 14.307
+    - type: recall_at_1
+      value: 37.239
+    - type: recall_at_10
+      value: 65.99000000000001
+    - type: recall_at_100
+      value: 82.99499999999999
+    - type: recall_at_1000
+      value: 94.128
+    - type: recall_at_3
+      value: 52.382
+    - type: recall_at_5
+      value: 57.648999999999994
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackGisRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.039
+    - type: map_at_10
+      value: 29.694
+    - type: map_at_100
+      value: 30.587999999999997
+    - type: map_at_1000
+      value: 30.692999999999998
+    - type: map_at_3
+      value: 27.708
+    - type: map_at_5
+      value: 28.774
+    - type: mrr_at_1
+      value: 24.633
+    - type: mrr_at_10
+      value: 31.478
+    - type: mrr_at_100
+      value: 32.299
+    - type: mrr_at_1000
+      value: 32.381
+    - type: mrr_at_3
+      value: 29.435
+    - type: mrr_at_5
+      value: 30.446
+    - type: ndcg_at_1
+      value: 24.633
+    - type: ndcg_at_10
+      value: 33.697
+    - type: ndcg_at_100
+      value: 38.080000000000005
+    - type: ndcg_at_1000
+      value: 40.812
+    - type: ndcg_at_3
+      value: 29.654000000000003
+    - type: ndcg_at_5
+      value: 31.474000000000004
+    - type: precision_at_1
+      value: 24.633
+    - type: precision_at_10
+      value: 5.0729999999999995
+    - type: precision_at_100
+      value: 0.753
+    - type: precision_at_1000
+      value: 0.10300000000000001
+    - type: precision_at_3
+      value: 12.279
+    - type: precision_at_5
+      value: 8.452
+    - type: recall_at_1
+      value: 23.039
+    - type: recall_at_10
+      value: 44.275999999999996
+    - type: recall_at_100
+      value: 64.4
+    - type: recall_at_1000
+      value: 85.135
+    - type: recall_at_3
+      value: 33.394
+    - type: recall_at_5
+      value: 37.687
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackMathematicaRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 13.594999999999999
+    - type: map_at_10
+      value: 19.933999999999997
+    - type: map_at_100
+      value: 20.966
+    - type: map_at_1000
+      value: 21.087
+    - type: map_at_3
+      value: 17.749000000000002
+    - type: map_at_5
+      value: 19.156000000000002
+    - type: mrr_at_1
+      value: 17.662
+    - type: mrr_at_10
+      value: 24.407
+    - type: mrr_at_100
+      value: 25.385
+    - type: mrr_at_1000
+      value: 25.465
+    - type: mrr_at_3
+      value: 22.056
+    - type: mrr_at_5
+      value: 23.630000000000003
+    - type: ndcg_at_1
+      value: 17.662
+    - type: ndcg_at_10
+      value: 24.391
+    - type: ndcg_at_100
+      value: 29.681
+    - type: ndcg_at_1000
+      value: 32.923
+    - type: ndcg_at_3
+      value: 20.271
+    - type: ndcg_at_5
+      value: 22.621
+    - type: precision_at_1
+      value: 17.662
+    - type: precision_at_10
+      value: 4.44
+    - type: precision_at_100
+      value: 0.8200000000000001
+    - type: precision_at_1000
+      value: 0.125
+    - type: precision_at_3
+      value: 9.577
+    - type: precision_at_5
+      value: 7.313
+    - type: recall_at_1
+      value: 13.594999999999999
+    - type: recall_at_10
+      value: 33.976
+    - type: recall_at_100
+      value: 57.43000000000001
+    - type: recall_at_1000
+      value: 80.958
+    - type: recall_at_3
+      value: 22.897000000000002
+    - type: recall_at_5
+      value: 28.714000000000002
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackPhysicsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.683
+    - type: map_at_10
+      value: 35.068
+    - type: map_at_100
+      value: 36.311
+    - type: map_at_1000
+      value: 36.436
+    - type: map_at_3
+      value: 32.371
+    - type: map_at_5
+      value: 33.761
+    - type: mrr_at_1
+      value: 32.435
+    - type: mrr_at_10
+      value: 40.721000000000004
+    - type: mrr_at_100
+      value: 41.535
+    - type: mrr_at_1000
+      value: 41.593
+    - type: mrr_at_3
+      value: 38.401999999999994
+    - type: mrr_at_5
+      value: 39.567
+    - type: ndcg_at_1
+      value: 32.435
+    - type: ndcg_at_10
+      value: 40.538000000000004
+    - type: ndcg_at_100
+      value: 45.963
+    - type: ndcg_at_1000
+      value: 48.400999999999996
+    - type: ndcg_at_3
+      value: 36.048
+    - type: ndcg_at_5
+      value: 37.899
+    - type: precision_at_1
+      value: 32.435
+    - type: precision_at_10
+      value: 7.1129999999999995
+    - type: precision_at_100
+      value: 1.162
+    - type: precision_at_1000
+      value: 0.156
+    - type: precision_at_3
+      value: 16.683
+    - type: precision_at_5
+      value: 11.684
+    - type: recall_at_1
+      value: 26.683
+    - type: recall_at_10
+      value: 51.517
+    - type: recall_at_100
+      value: 74.553
+    - type: recall_at_1000
+      value: 90.649
+    - type: recall_at_3
+      value: 38.495000000000005
+    - type: recall_at_5
+      value: 43.495
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackProgrammersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.186
+    - type: map_at_10
+      value: 31.972
+    - type: map_at_100
+      value: 33.117000000000004
+    - type: map_at_1000
+      value: 33.243
+    - type: map_at_3
+      value: 29.423
+    - type: map_at_5
+      value: 30.847
+    - type: mrr_at_1
+      value: 29.794999999999998
+    - type: mrr_at_10
+      value: 36.767
+    - type: mrr_at_100
+      value: 37.645
+    - type: mrr_at_1000
+      value: 37.716
+    - type: mrr_at_3
+      value: 34.513
+    - type: mrr_at_5
+      value: 35.791000000000004
+    - type: ndcg_at_1
+      value: 29.794999999999998
+    - type: ndcg_at_10
+      value: 36.786
+    - type: ndcg_at_100
+      value: 41.94
+    - type: ndcg_at_1000
+      value: 44.830999999999996
+    - type: ndcg_at_3
+      value: 32.504
+    - type: ndcg_at_5
+      value: 34.404
+    - type: precision_at_1
+      value: 29.794999999999998
+    - type: precision_at_10
+      value: 6.518
+    - type: precision_at_100
+      value: 1.0659999999999998
+    - type: precision_at_1000
+      value: 0.149
+    - type: precision_at_3
+      value: 15.296999999999999
+    - type: precision_at_5
+      value: 10.731
+    - type: recall_at_1
+      value: 24.186
+    - type: recall_at_10
+      value: 46.617
+    - type: recall_at_100
+      value: 68.75
+    - type: recall_at_1000
+      value: 88.864
+    - type: recall_at_3
+      value: 34.199
+    - type: recall_at_5
+      value: 39.462
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.22083333333333
+    - type: map_at_10
+      value: 31.606666666666662
+    - type: map_at_100
+      value: 32.6195
+    - type: map_at_1000
+      value: 32.739999999999995
+    - type: map_at_3
+      value: 29.37825
+    - type: map_at_5
+      value: 30.596083333333336
+    - type: mrr_at_1
+      value: 28.607916666666668
+    - type: mrr_at_10
+      value: 35.54591666666666
+    - type: mrr_at_100
+      value: 36.33683333333333
+    - type: mrr_at_1000
+      value: 36.40624999999999
+    - type: mrr_at_3
+      value: 33.526250000000005
+    - type: mrr_at_5
+      value: 34.6605
+    - type: ndcg_at_1
+      value: 28.607916666666668
+    - type: ndcg_at_10
+      value: 36.07966666666667
+    - type: ndcg_at_100
+      value: 40.73308333333333
+    - type: ndcg_at_1000
+      value: 43.40666666666666
+    - type: ndcg_at_3
+      value: 32.23525
+    - type: ndcg_at_5
+      value: 33.97083333333333
+    - type: precision_at_1
+      value: 28.607916666666668
+    - type: precision_at_10
+      value: 6.120333333333335
+    - type: precision_at_100
+      value: 0.9921666666666668
+    - type: precision_at_1000
+      value: 0.14091666666666666
+    - type: precision_at_3
+      value: 14.54975
+    - type: precision_at_5
+      value: 10.153166666666667
+    - type: recall_at_1
+      value: 24.22083333333333
+    - type: recall_at_10
+      value: 45.49183333333334
+    - type: recall_at_100
+      value: 66.28133333333332
+    - type: recall_at_1000
+      value: 85.16541666666667
+    - type: recall_at_3
+      value: 34.6485
+    - type: recall_at_5
+      value: 39.229749999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackStatsRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 21.842
+    - type: map_at_10
+      value: 27.573999999999998
+    - type: map_at_100
+      value: 28.410999999999998
+    - type: map_at_1000
+      value: 28.502
+    - type: map_at_3
+      value: 25.921
+    - type: map_at_5
+      value: 26.888
+    - type: mrr_at_1
+      value: 24.08
+    - type: mrr_at_10
+      value: 29.915999999999997
+    - type: mrr_at_100
+      value: 30.669
+    - type: mrr_at_1000
+      value: 30.746000000000002
+    - type: mrr_at_3
+      value: 28.349000000000004
+    - type: mrr_at_5
+      value: 29.246
+    - type: ndcg_at_1
+      value: 24.08
+    - type: ndcg_at_10
+      value: 30.898999999999997
+    - type: ndcg_at_100
+      value: 35.272999999999996
+    - type: ndcg_at_1000
+      value: 37.679
+    - type: ndcg_at_3
+      value: 27.881
+    - type: ndcg_at_5
+      value: 29.432000000000002
+    - type: precision_at_1
+      value: 24.08
+    - type: precision_at_10
+      value: 4.678
+    - type: precision_at_100
+      value: 0.744
+    - type: precision_at_1000
+      value: 0.10300000000000001
+    - type: precision_at_3
+      value: 11.860999999999999
+    - type: precision_at_5
+      value: 8.16
+    - type: recall_at_1
+      value: 21.842
+    - type: recall_at_10
+      value: 38.66
+    - type: recall_at_100
+      value: 59.169000000000004
+    - type: recall_at_1000
+      value: 76.887
+    - type: recall_at_3
+      value: 30.532999999999998
+    - type: recall_at_5
+      value: 34.354
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackTexRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 17.145
+    - type: map_at_10
+      value: 22.729
+    - type: map_at_100
+      value: 23.574
+    - type: map_at_1000
+      value: 23.695
+    - type: map_at_3
+      value: 21.044
+    - type: map_at_5
+      value: 21.981
+    - type: mrr_at_1
+      value: 20.888
+    - type: mrr_at_10
+      value: 26.529000000000003
+    - type: mrr_at_100
+      value: 27.308
+    - type: mrr_at_1000
+      value: 27.389000000000003
+    - type: mrr_at_3
+      value: 24.868000000000002
+    - type: mrr_at_5
+      value: 25.825
+    - type: ndcg_at_1
+      value: 20.888
+    - type: ndcg_at_10
+      value: 26.457000000000004
+    - type: ndcg_at_100
+      value: 30.764000000000003
+    - type: ndcg_at_1000
+      value: 33.825
+    - type: ndcg_at_3
+      value: 23.483999999999998
+    - type: ndcg_at_5
+      value: 24.836
+    - type: precision_at_1
+      value: 20.888
+    - type: precision_at_10
+      value: 4.58
+    - type: precision_at_100
+      value: 0.784
+    - type: precision_at_1000
+      value: 0.121
+    - type: precision_at_3
+      value: 10.874
+    - type: precision_at_5
+      value: 7.639
+    - type: recall_at_1
+      value: 17.145
+    - type: recall_at_10
+      value: 33.938
+    - type: recall_at_100
+      value: 53.672
+    - type: recall_at_1000
+      value: 76.023
+    - type: recall_at_3
+      value: 25.363000000000003
+    - type: recall_at_5
+      value: 29.023
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackUnixRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 24.275
+    - type: map_at_10
+      value: 30.438
+    - type: map_at_100
+      value: 31.489
+    - type: map_at_1000
+      value: 31.601000000000003
+    - type: map_at_3
+      value: 28.647
+    - type: map_at_5
+      value: 29.660999999999998
+    - type: mrr_at_1
+      value: 28.077999999999996
+    - type: mrr_at_10
+      value: 34.098
+    - type: mrr_at_100
+      value: 35.025
+    - type: mrr_at_1000
+      value: 35.109
+    - type: mrr_at_3
+      value: 32.4
+    - type: mrr_at_5
+      value: 33.379999999999995
+    - type: ndcg_at_1
+      value: 28.077999999999996
+    - type: ndcg_at_10
+      value: 34.271
+    - type: ndcg_at_100
+      value: 39.352
+    - type: ndcg_at_1000
+      value: 42.199
+    - type: ndcg_at_3
+      value: 30.978
+    - type: ndcg_at_5
+      value: 32.498
+    - type: precision_at_1
+      value: 28.077999999999996
+    - type: precision_at_10
+      value: 5.345
+    - type: precision_at_100
+      value: 0.897
+    - type: precision_at_1000
+      value: 0.125
+    - type: precision_at_3
+      value: 13.526
+    - type: precision_at_5
+      value: 9.16
+    - type: recall_at_1
+      value: 24.275
+    - type: recall_at_10
+      value: 42.362
+    - type: recall_at_100
+      value: 64.461
+    - type: recall_at_1000
+      value: 84.981
+    - type: recall_at_3
+      value: 33.249
+    - type: recall_at_5
+      value: 37.214999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWebmastersRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 22.358
+    - type: map_at_10
+      value: 30.062
+    - type: map_at_100
+      value: 31.189
+    - type: map_at_1000
+      value: 31.386999999999997
+    - type: map_at_3
+      value: 27.672
+    - type: map_at_5
+      value: 28.76
+    - type: mrr_at_1
+      value: 26.877000000000002
+    - type: mrr_at_10
+      value: 33.948
+    - type: mrr_at_100
+      value: 34.746
+    - type: mrr_at_1000
+      value: 34.816
+    - type: mrr_at_3
+      value: 31.884
+    - type: mrr_at_5
+      value: 33.001000000000005
+    - type: ndcg_at_1
+      value: 26.877000000000002
+    - type: ndcg_at_10
+      value: 34.977000000000004
+    - type: ndcg_at_100
+      value: 39.753
+    - type: ndcg_at_1000
+      value: 42.866
+    - type: ndcg_at_3
+      value: 30.956
+    - type: ndcg_at_5
+      value: 32.381
+    - type: precision_at_1
+      value: 26.877000000000002
+    - type: precision_at_10
+      value: 6.7
+    - type: precision_at_100
+      value: 1.287
+    - type: precision_at_1000
+      value: 0.215
+    - type: precision_at_3
+      value: 14.360999999999999
+    - type: precision_at_5
+      value: 10.119
+    - type: recall_at_1
+      value: 22.358
+    - type: recall_at_10
+      value: 44.183
+    - type: recall_at_100
+      value: 67.14
+    - type: recall_at_1000
+      value: 87.53999999999999
+    - type: recall_at_3
+      value: 32.79
+    - type: recall_at_5
+      value: 36.829
+  - task:
+      type: Retrieval
+    dataset:
+      type: BeIR/cqadupstack
+      name: MTEB CQADupstackWordpressRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 19.198999999999998
+    - type: map_at_10
+      value: 25.229000000000003
+    - type: map_at_100
+      value: 26.003
+    - type: map_at_1000
+      value: 26.111
+    - type: map_at_3
+      value: 23.442
+    - type: map_at_5
+      value: 24.343
+    - type: mrr_at_1
+      value: 21.072
+    - type: mrr_at_10
+      value: 27.02
+    - type: mrr_at_100
+      value: 27.735
+    - type: mrr_at_1000
+      value: 27.815
+    - type: mrr_at_3
+      value: 25.416
+    - type: mrr_at_5
+      value: 26.173999999999996
+    - type: ndcg_at_1
+      value: 21.072
+    - type: ndcg_at_10
+      value: 28.862
+    - type: ndcg_at_100
+      value: 33.043
+    - type: ndcg_at_1000
+      value: 36.003
+    - type: ndcg_at_3
+      value: 25.35
+    - type: ndcg_at_5
+      value: 26.773000000000003
+    - type: precision_at_1
+      value: 21.072
+    - type: precision_at_10
+      value: 4.436
+    - type: precision_at_100
+      value: 0.713
+    - type: precision_at_1000
+      value: 0.106
+    - type: precision_at_3
+      value: 10.659
+    - type: precision_at_5
+      value: 7.32
+    - type: recall_at_1
+      value: 19.198999999999998
+    - type: recall_at_10
+      value: 38.376
+    - type: recall_at_100
+      value: 58.36900000000001
+    - type: recall_at_1000
+      value: 80.92099999999999
+    - type: recall_at_3
+      value: 28.715000000000003
+    - type: recall_at_5
+      value: 32.147
+  - task:
+      type: Retrieval
+    dataset:
+      type: climate-fever
+      name: MTEB ClimateFEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.9319999999999995
+    - type: map_at_10
+      value: 10.483
+    - type: map_at_100
+      value: 11.97
+    - type: map_at_1000
+      value: 12.171999999999999
+    - type: map_at_3
+      value: 8.477
+    - type: map_at_5
+      value: 9.495000000000001
+    - type: mrr_at_1
+      value: 13.094
+    - type: mrr_at_10
+      value: 21.282
+    - type: mrr_at_100
+      value: 22.556
+    - type: mrr_at_1000
+      value: 22.628999999999998
+    - type: mrr_at_3
+      value: 18.218999999999998
+    - type: mrr_at_5
+      value: 19.900000000000002
+    - type: ndcg_at_1
+      value: 13.094
+    - type: ndcg_at_10
+      value: 15.811
+    - type: ndcg_at_100
+      value: 23.035
+    - type: ndcg_at_1000
+      value: 27.089999999999996
+    - type: ndcg_at_3
+      value: 11.905000000000001
+    - type: ndcg_at_5
+      value: 13.377
+    - type: precision_at_1
+      value: 13.094
+    - type: precision_at_10
+      value: 5.225
+    - type: precision_at_100
+      value: 1.2970000000000002
+    - type: precision_at_1000
+      value: 0.203
+    - type: precision_at_3
+      value: 8.86
+    - type: precision_at_5
+      value: 7.309
+    - type: recall_at_1
+      value: 5.9319999999999995
+    - type: recall_at_10
+      value: 20.305
+    - type: recall_at_100
+      value: 46.314
+    - type: recall_at_1000
+      value: 69.612
+    - type: recall_at_3
+      value: 11.21
+    - type: recall_at_5
+      value: 14.773
+  - task:
+      type: Retrieval
+    dataset:
+      type: dbpedia-entity
+      name: MTEB DBPedia
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 8.674
+    - type: map_at_10
+      value: 17.822
+    - type: map_at_100
+      value: 24.794
+    - type: map_at_1000
+      value: 26.214
+    - type: map_at_3
+      value: 12.690999999999999
+    - type: map_at_5
+      value: 15.033
+    - type: mrr_at_1
+      value: 61.75000000000001
+    - type: mrr_at_10
+      value: 71.58
+    - type: mrr_at_100
+      value: 71.923
+    - type: mrr_at_1000
+      value: 71.932
+    - type: mrr_at_3
+      value: 70.125
+    - type: mrr_at_5
+      value: 71.038
+    - type: ndcg_at_1
+      value: 51
+    - type: ndcg_at_10
+      value: 38.637
+    - type: ndcg_at_100
+      value: 42.398
+    - type: ndcg_at_1000
+      value: 48.962
+    - type: ndcg_at_3
+      value: 43.29
+    - type: ndcg_at_5
+      value: 40.763
+    - type: precision_at_1
+      value: 61.75000000000001
+    - type: precision_at_10
+      value: 30.125
+    - type: precision_at_100
+      value: 9.53
+    - type: precision_at_1000
+      value: 1.9619999999999997
+    - type: precision_at_3
+      value: 45.583
+    - type: precision_at_5
+      value: 38.95
+    - type: recall_at_1
+      value: 8.674
+    - type: recall_at_10
+      value: 23.122
+    - type: recall_at_100
+      value: 47.46
+    - type: recall_at_1000
+      value: 67.662
+    - type: recall_at_3
+      value: 13.946
+    - type: recall_at_5
+      value: 17.768
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/emotion
+      name: MTEB EmotionClassification
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 46.86000000000001
+    - type: f1
+      value: 41.343580452760776
+  - task:
+      type: Retrieval
+    dataset:
+      type: fever
+      name: MTEB FEVER
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 36.609
+    - type: map_at_10
+      value: 47.552
+    - type: map_at_100
+      value: 48.283
+    - type: map_at_1000
+      value: 48.321
+    - type: map_at_3
+      value: 44.869
+    - type: map_at_5
+      value: 46.509
+    - type: mrr_at_1
+      value: 39.214
+    - type: mrr_at_10
+      value: 50.434999999999995
+    - type: mrr_at_100
+      value: 51.122
+    - type: mrr_at_1000
+      value: 51.151
+    - type: mrr_at_3
+      value: 47.735
+    - type: mrr_at_5
+      value: 49.394
+    - type: ndcg_at_1
+      value: 39.214
+    - type: ndcg_at_10
+      value: 53.52400000000001
+    - type: ndcg_at_100
+      value: 56.997
+    - type: ndcg_at_1000
+      value: 57.975
+    - type: ndcg_at_3
+      value: 48.173
+    - type: ndcg_at_5
+      value: 51.05800000000001
+    - type: precision_at_1
+      value: 39.214
+    - type: precision_at_10
+      value: 7.573
+    - type: precision_at_100
+      value: 0.9440000000000001
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 19.782
+    - type: precision_at_5
+      value: 13.453000000000001
+    - type: recall_at_1
+      value: 36.609
+    - type: recall_at_10
+      value: 69.247
+    - type: recall_at_100
+      value: 84.99600000000001
+    - type: recall_at_1000
+      value: 92.40899999999999
+    - type: recall_at_3
+      value: 54.856
+    - type: recall_at_5
+      value: 61.797000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      type: fiqa
+      name: MTEB FiQA2018
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 16.466
+    - type: map_at_10
+      value: 27.060000000000002
+    - type: map_at_100
+      value: 28.511999999999997
+    - type: map_at_1000
+      value: 28.693
+    - type: map_at_3
+      value: 22.777
+    - type: map_at_5
+      value: 25.086000000000002
+    - type: mrr_at_1
+      value: 32.716
+    - type: mrr_at_10
+      value: 41.593999999999994
+    - type: mrr_at_100
+      value: 42.370000000000005
+    - type: mrr_at_1000
+      value: 42.419000000000004
+    - type: mrr_at_3
+      value: 38.143
+    - type: mrr_at_5
+      value: 40.288000000000004
+    - type: ndcg_at_1
+      value: 32.716
+    - type: ndcg_at_10
+      value: 34.795
+    - type: ndcg_at_100
+      value: 40.58
+    - type: ndcg_at_1000
+      value: 43.993
+    - type: ndcg_at_3
+      value: 29.573
+    - type: ndcg_at_5
+      value: 31.583
+    - type: precision_at_1
+      value: 32.716
+    - type: precision_at_10
+      value: 9.937999999999999
+    - type: precision_at_100
+      value: 1.585
+    - type: precision_at_1000
+      value: 0.22
+    - type: precision_at_3
+      value: 19.496
+    - type: precision_at_5
+      value: 15.247
+    - type: recall_at_1
+      value: 16.466
+    - type: recall_at_10
+      value: 42.886
+    - type: recall_at_100
+      value: 64.724
+    - type: recall_at_1000
+      value: 85.347
+    - type: recall_at_3
+      value: 26.765
+    - type: recall_at_5
+      value: 33.603
+  - task:
+      type: Retrieval
+    dataset:
+      type: hotpotqa
+      name: MTEB HotpotQA
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 33.025
+    - type: map_at_10
+      value: 47.343
+    - type: map_at_100
+      value: 48.207
+    - type: map_at_1000
+      value: 48.281
+    - type: map_at_3
+      value: 44.519
+    - type: map_at_5
+      value: 46.217000000000006
+    - type: mrr_at_1
+      value: 66.05
+    - type: mrr_at_10
+      value: 72.94699999999999
+    - type: mrr_at_100
+      value: 73.289
+    - type: mrr_at_1000
+      value: 73.30499999999999
+    - type: mrr_at_3
+      value: 71.686
+    - type: mrr_at_5
+      value: 72.491
+    - type: ndcg_at_1
+      value: 66.05
+    - type: ndcg_at_10
+      value: 56.338
+    - type: ndcg_at_100
+      value: 59.599999999999994
+    - type: ndcg_at_1000
+      value: 61.138000000000005
+    - type: ndcg_at_3
+      value: 52.034000000000006
+    - type: ndcg_at_5
+      value: 54.352000000000004
+    - type: precision_at_1
+      value: 66.05
+    - type: precision_at_10
+      value: 11.693000000000001
+    - type: precision_at_100
+      value: 1.425
+    - type: precision_at_1000
+      value: 0.163
+    - type: precision_at_3
+      value: 32.613
+    - type: precision_at_5
+      value: 21.401999999999997
+    - type: recall_at_1
+      value: 33.025
+    - type: recall_at_10
+      value: 58.467
+    - type: recall_at_100
+      value: 71.242
+    - type: recall_at_1000
+      value: 81.452
+    - type: recall_at_3
+      value: 48.92
+    - type: recall_at_5
+      value: 53.504
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/imdb
+      name: MTEB ImdbClassification
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 75.5492
+    - type: ap
+      value: 69.42911637216271
+    - type: f1
+      value: 75.39113704261024
+  - task:
+      type: Retrieval
+    dataset:
+      type: msmarco
+      name: MTEB MSMARCO
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.173
+    - type: map_at_10
+      value: 35.453
+    - type: map_at_100
+      value: 36.573
+    - type: map_at_1000
+      value: 36.620999999999995
+    - type: map_at_3
+      value: 31.655
+    - type: map_at_5
+      value: 33.823
+    - type: mrr_at_1
+      value: 23.868000000000002
+    - type: mrr_at_10
+      value: 36.085
+    - type: mrr_at_100
+      value: 37.15
+    - type: mrr_at_1000
+      value: 37.193
+    - type: mrr_at_3
+      value: 32.376
+    - type: mrr_at_5
+      value: 34.501
+    - type: ndcg_at_1
+      value: 23.854
+    - type: ndcg_at_10
+      value: 42.33
+    - type: ndcg_at_100
+      value: 47.705999999999996
+    - type: ndcg_at_1000
+      value: 48.91
+    - type: ndcg_at_3
+      value: 34.604
+    - type: ndcg_at_5
+      value: 38.473
+    - type: precision_at_1
+      value: 23.854
+    - type: precision_at_10
+      value: 6.639
+    - type: precision_at_100
+      value: 0.932
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 14.685
+    - type: precision_at_5
+      value: 10.782
+    - type: recall_at_1
+      value: 23.173
+    - type: recall_at_10
+      value: 63.441
+    - type: recall_at_100
+      value: 88.25
+    - type: recall_at_1000
+      value: 97.438
+    - type: recall_at_3
+      value: 42.434
+    - type: recall_at_5
+      value: 51.745
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_domain
+      name: MTEB MTOPDomainClassification (en)
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 92.05426356589147
+    - type: f1
+      value: 91.88068588063942
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/mtop_intent
+      name: MTEB MTOPIntentClassification (en)
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 73.23985408116735
+    - type: f1
+      value: 55.858906745287506
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_intent
+      name: MTEB MassiveIntentClassification (en)
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 72.21923335574984
+    - type: f1
+      value: 70.0174116204253
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/amazon_massive_scenario
+      name: MTEB MassiveScenarioClassification (en)
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 75.77673167451245
+    - type: f1
+      value: 75.44811354778666
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-p2p
+      name: MTEB MedrxivClusteringP2P
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 31.340414710728737
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/medrxiv-clustering-s2s
+      name: MTEB MedrxivClusteringS2S
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 28.196676760061578
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/mind_small
+      name: MTEB MindSmallReranking
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 29.564149683482206
+    - type: mrr
+      value: 30.28995474250486
+  - task:
+      type: Retrieval
+    dataset:
+      type: nfcorpus
+      name: MTEB NFCorpus
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 5.93
+    - type: map_at_10
+      value: 12.828000000000001
+    - type: map_at_100
+      value: 15.501000000000001
+    - type: map_at_1000
+      value: 16.791
+    - type: map_at_3
+      value: 9.727
+    - type: map_at_5
+      value: 11.318999999999999
+    - type: mrr_at_1
+      value: 47.678
+    - type: mrr_at_10
+      value: 55.893
+    - type: mrr_at_100
+      value: 56.491
+    - type: mrr_at_1000
+      value: 56.53
+    - type: mrr_at_3
+      value: 54.386
+    - type: mrr_at_5
+      value: 55.516
+    - type: ndcg_at_1
+      value: 45.975
+    - type: ndcg_at_10
+      value: 33.928999999999995
+    - type: ndcg_at_100
+      value: 30.164
+    - type: ndcg_at_1000
+      value: 38.756
+    - type: ndcg_at_3
+      value: 41.077000000000005
+    - type: ndcg_at_5
+      value: 38.415
+    - type: precision_at_1
+      value: 47.678
+    - type: precision_at_10
+      value: 24.365000000000002
+    - type: precision_at_100
+      value: 7.344
+    - type: precision_at_1000
+      value: 1.994
+    - type: precision_at_3
+      value: 38.184000000000005
+    - type: precision_at_5
+      value: 33.003
+    - type: recall_at_1
+      value: 5.93
+    - type: recall_at_10
+      value: 16.239
+    - type: recall_at_100
+      value: 28.782999999999998
+    - type: recall_at_1000
+      value: 60.11
+    - type: recall_at_3
+      value: 10.700999999999999
+    - type: recall_at_5
+      value: 13.584
+  - task:
+      type: Retrieval
+    dataset:
+      type: nq
+      name: MTEB NQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 36.163000000000004
+    - type: map_at_10
+      value: 51.520999999999994
+    - type: map_at_100
+      value: 52.449
+    - type: map_at_1000
+      value: 52.473000000000006
+    - type: map_at_3
+      value: 47.666
+    - type: map_at_5
+      value: 50.043000000000006
+    - type: mrr_at_1
+      value: 40.266999999999996
+    - type: mrr_at_10
+      value: 54.074
+    - type: mrr_at_100
+      value: 54.722
+    - type: mrr_at_1000
+      value: 54.739000000000004
+    - type: mrr_at_3
+      value: 51.043000000000006
+    - type: mrr_at_5
+      value: 52.956
+    - type: ndcg_at_1
+      value: 40.238
+    - type: ndcg_at_10
+      value: 58.73199999999999
+    - type: ndcg_at_100
+      value: 62.470000000000006
+    - type: ndcg_at_1000
+      value: 63.083999999999996
+    - type: ndcg_at_3
+      value: 51.672
+    - type: ndcg_at_5
+      value: 55.564
+    - type: precision_at_1
+      value: 40.238
+    - type: precision_at_10
+      value: 9.279
+    - type: precision_at_100
+      value: 1.139
+    - type: precision_at_1000
+      value: 0.12
+    - type: precision_at_3
+      value: 23.078000000000003
+    - type: precision_at_5
+      value: 16.176
+    - type: recall_at_1
+      value: 36.163000000000004
+    - type: recall_at_10
+      value: 77.88199999999999
+    - type: recall_at_100
+      value: 93.83399999999999
+    - type: recall_at_1000
+      value: 98.465
+    - type: recall_at_3
+      value: 59.857000000000006
+    - type: recall_at_5
+      value: 68.73599999999999
+  - task:
+      type: Retrieval
+    dataset:
+      type: quora
+      name: MTEB QuoraRetrieval
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 70.344
+    - type: map_at_10
+      value: 83.907
+    - type: map_at_100
+      value: 84.536
+    - type: map_at_1000
+      value: 84.557
+    - type: map_at_3
+      value: 80.984
+    - type: map_at_5
+      value: 82.844
+    - type: mrr_at_1
+      value: 81.02000000000001
+    - type: mrr_at_10
+      value: 87.158
+    - type: mrr_at_100
+      value: 87.268
+    - type: mrr_at_1000
+      value: 87.26899999999999
+    - type: mrr_at_3
+      value: 86.17
+    - type: mrr_at_5
+      value: 86.87
+    - type: ndcg_at_1
+      value: 81.02000000000001
+    - type: ndcg_at_10
+      value: 87.70700000000001
+    - type: ndcg_at_100
+      value: 89.004
+    - type: ndcg_at_1000
+      value: 89.139
+    - type: ndcg_at_3
+      value: 84.841
+    - type: ndcg_at_5
+      value: 86.455
+    - type: precision_at_1
+      value: 81.02000000000001
+    - type: precision_at_10
+      value: 13.248999999999999
+    - type: precision_at_100
+      value: 1.516
+    - type: precision_at_1000
+      value: 0.156
+    - type: precision_at_3
+      value: 36.963
+    - type: precision_at_5
+      value: 24.33
+    - type: recall_at_1
+      value: 70.344
+    - type: recall_at_10
+      value: 94.75099999999999
+    - type: recall_at_100
+      value: 99.30499999999999
+    - type: recall_at_1000
+      value: 99.928
+    - type: recall_at_3
+      value: 86.506
+    - type: recall_at_5
+      value: 91.083
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering
+      name: MTEB RedditClustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 42.873718018378305
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/reddit-clustering-p2p
+      name: MTEB RedditClusteringP2P
+      config: default
+      split: test
+      revision: 282350215ef01743dc01b456c7f5241fa8937f16
+    metrics:
+    - type: v_measure
+      value: 56.39477366450528
+  - task:
+      type: Retrieval
+    dataset:
+      type: scidocs
+      name: MTEB SCIDOCS
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 3.868
+    - type: map_at_10
+      value: 9.611
+    - type: map_at_100
+      value: 11.087
+    - type: map_at_1000
+      value: 11.332
+    - type: map_at_3
+      value: 6.813
+    - type: map_at_5
+      value: 8.233
+    - type: mrr_at_1
+      value: 19
+    - type: mrr_at_10
+      value: 28.457
+    - type: mrr_at_100
+      value: 29.613
+    - type: mrr_at_1000
+      value: 29.695
+    - type: mrr_at_3
+      value: 25.55
+    - type: mrr_at_5
+      value: 27.29
+    - type: ndcg_at_1
+      value: 19
+    - type: ndcg_at_10
+      value: 16.419
+    - type: ndcg_at_100
+      value: 22.817999999999998
+    - type: ndcg_at_1000
+      value: 27.72
+    - type: ndcg_at_3
+      value: 15.379000000000001
+    - type: ndcg_at_5
+      value: 13.645
+    - type: precision_at_1
+      value: 19
+    - type: precision_at_10
+      value: 8.540000000000001
+    - type: precision_at_100
+      value: 1.7819999999999998
+    - type: precision_at_1000
+      value: 0.297
+    - type: precision_at_3
+      value: 14.267
+    - type: precision_at_5
+      value: 12.04
+    - type: recall_at_1
+      value: 3.868
+    - type: recall_at_10
+      value: 17.288
+    - type: recall_at_100
+      value: 36.144999999999996
+    - type: recall_at_1000
+      value: 60.199999999999996
+    - type: recall_at_3
+      value: 8.688
+    - type: recall_at_5
+      value: 12.198
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sickr-sts
+      name: MTEB SICK-R
+      config: default
+      split: test
+      revision: a6ea5a8cab320b040a23452cc28066d9beae2cee
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.96614722598582
+    - type: cos_sim_spearman
+      value: 78.9003023008781
+    - type: euclidean_pearson
+      value: 81.01829384436505
+    - type: euclidean_spearman
+      value: 78.93248416788914
+    - type: manhattan_pearson
+      value: 81.1665428926402
+    - type: manhattan_spearman
+      value: 78.93264116287453
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts12-sts
+      name: MTEB STS12
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.54613363895993
+    - type: cos_sim_spearman
+      value: 75.1883451602451
+    - type: euclidean_pearson
+      value: 79.70320886899894
+    - type: euclidean_spearman
+      value: 74.5917140136796
+    - type: manhattan_pearson
+      value: 79.82157067185999
+    - type: manhattan_spearman
+      value: 74.74185720594735
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts13-sts
+      name: MTEB STS13
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.30430156721782
+    - type: cos_sim_spearman
+      value: 81.79962989974364
+    - type: euclidean_pearson
+      value: 80.89058823224924
+    - type: euclidean_spearman
+      value: 81.35929372984597
+    - type: manhattan_pearson
+      value: 81.12204370487478
+    - type: manhattan_spearman
+      value: 81.6248963282232
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts14-sts
+      name: MTEB STS14
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.13064504403134
+    - type: cos_sim_spearman
+      value: 78.48371403924872
+    - type: euclidean_pearson
+      value: 80.16794919665591
+    - type: euclidean_spearman
+      value: 78.29216082221699
+    - type: manhattan_pearson
+      value: 80.22308565207301
+    - type: manhattan_spearman
+      value: 78.37829229948022
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts15-sts
+      name: MTEB STS15
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.52918899541099
+    - type: cos_sim_spearman
+      value: 87.49276894673142
+    - type: euclidean_pearson
+      value: 86.77440570164254
+    - type: euclidean_spearman
+      value: 87.5753295736756
+    - type: manhattan_pearson
+      value: 86.86098573892133
+    - type: manhattan_spearman
+      value: 87.65848591821947
+  - task:
+      type: STS
+    dataset:
+      type: mteb/sts16-sts
+      name: MTEB STS16
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 82.86805307244882
+    - type: cos_sim_spearman
+      value: 84.58066253757511
+    - type: euclidean_pearson
+      value: 84.38377000876991
+    - type: euclidean_spearman
+      value: 85.1837278784528
+    - type: manhattan_pearson
+      value: 84.41903291363842
+    - type: manhattan_spearman
+      value: 85.19023736251052
+  - 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: 86.77218560282436
+    - type: cos_sim_spearman
+      value: 87.94243515296604
+    - type: euclidean_pearson
+      value: 88.22800939214864
+    - type: euclidean_spearman
+      value: 87.91106839439841
+    - type: manhattan_pearson
+      value: 88.17063269848741
+    - type: manhattan_spearman
+      value: 87.72751904126062
+  - 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: 60.40731554300387
+    - type: cos_sim_spearman
+      value: 63.76300532966479
+    - type: euclidean_pearson
+      value: 62.94727878229085
+    - type: euclidean_spearman
+      value: 63.678039531461216
+    - type: manhattan_pearson
+      value: 63.00661039863549
+    - type: manhattan_spearman
+      value: 63.6282591984376
+  - task:
+      type: STS
+    dataset:
+      type: mteb/stsbenchmark-sts
+      name: MTEB STSBenchmark
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 84.92731569745344
+    - type: cos_sim_spearman
+      value: 86.36336704300167
+    - type: euclidean_pearson
+      value: 86.09122224841195
+    - type: euclidean_spearman
+      value: 86.2116149319238
+    - type: manhattan_pearson
+      value: 86.07879456717032
+    - type: manhattan_spearman
+      value: 86.2022069635119
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/scidocs-reranking
+      name: MTEB SciDocsRR
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 79.75976311752326
+    - type: mrr
+      value: 94.15782837351466
+  - task:
+      type: Retrieval
+    dataset:
+      type: scifact
+      name: MTEB SciFact
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 51.193999999999996
+    - type: map_at_10
+      value: 61.224999999999994
+    - type: map_at_100
+      value: 62.031000000000006
+    - type: map_at_1000
+      value: 62.066
+    - type: map_at_3
+      value: 59.269000000000005
+    - type: map_at_5
+      value: 60.159
+    - type: mrr_at_1
+      value: 53.667
+    - type: mrr_at_10
+      value: 62.74999999999999
+    - type: mrr_at_100
+      value: 63.39399999999999
+    - type: mrr_at_1000
+      value: 63.425
+    - type: mrr_at_3
+      value: 61.389
+    - type: mrr_at_5
+      value: 61.989000000000004
+    - type: ndcg_at_1
+      value: 53.667
+    - type: ndcg_at_10
+      value: 65.596
+    - type: ndcg_at_100
+      value: 68.906
+    - type: ndcg_at_1000
+      value: 69.78999999999999
+    - type: ndcg_at_3
+      value: 62.261
+    - type: ndcg_at_5
+      value: 63.453
+    - type: precision_at_1
+      value: 53.667
+    - type: precision_at_10
+      value: 8.667
+    - type: precision_at_100
+      value: 1.04
+    - type: precision_at_1000
+      value: 0.11100000000000002
+    - type: precision_at_3
+      value: 24.556
+    - type: precision_at_5
+      value: 15.6
+    - type: recall_at_1
+      value: 51.193999999999996
+    - type: recall_at_10
+      value: 77.156
+    - type: recall_at_100
+      value: 91.43299999999999
+    - type: recall_at_1000
+      value: 98.333
+    - type: recall_at_3
+      value: 67.994
+    - type: recall_at_5
+      value: 71.14399999999999
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/sprintduplicatequestions-pairclassification
+      name: MTEB SprintDuplicateQuestions
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.81485148514851
+    - type: cos_sim_ap
+      value: 95.28896513388551
+    - type: cos_sim_f1
+      value: 90.43478260869566
+    - type: cos_sim_precision
+      value: 92.56544502617801
+    - type: cos_sim_recall
+      value: 88.4
+    - type: dot_accuracy
+      value: 99.30594059405941
+    - type: dot_ap
+      value: 61.6432597455472
+    - type: dot_f1
+      value: 59.46481665014866
+    - type: dot_precision
+      value: 58.93909626719057
+    - type: dot_recall
+      value: 60
+    - type: euclidean_accuracy
+      value: 99.81980198019802
+    - type: euclidean_ap
+      value: 95.21411049527
+    - type: euclidean_f1
+      value: 91.06090373280944
+    - type: euclidean_precision
+      value: 89.47876447876449
+    - type: euclidean_recall
+      value: 92.7
+    - type: manhattan_accuracy
+      value: 99.81782178217821
+    - type: manhattan_ap
+      value: 95.32449994414968
+    - type: manhattan_f1
+      value: 90.86395233366436
+    - type: manhattan_precision
+      value: 90.23668639053254
+    - type: manhattan_recall
+      value: 91.5
+    - type: max_accuracy
+      value: 99.81980198019802
+    - type: max_ap
+      value: 95.32449994414968
+    - type: max_f1
+      value: 91.06090373280944
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering
+      name: MTEB StackExchangeClustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 59.08045614613064
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/stackexchange-clustering-p2p
+      name: MTEB StackExchangeClusteringP2P
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 30.297802606804748
+  - task:
+      type: Reranking
+    dataset:
+      type: mteb/stackoverflowdupquestions-reranking
+      name: MTEB StackOverflowDupQuestions
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 49.12801740706292
+    - type: mrr
+      value: 50.05592956879722
+  - task:
+      type: Summarization
+    dataset:
+      type: mteb/summeval
+      name: MTEB SummEval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 31.523347880124497
+    - type: cos_sim_spearman
+      value: 31.388214436391014
+    - type: dot_pearson
+      value: 24.55403435439901
+    - type: dot_spearman
+      value: 23.50153210841191
+  - task:
+      type: Retrieval
+    dataset:
+      type: trec-covid
+      name: MTEB TRECCOVID
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 0.243
+    - type: map_at_10
+      value: 1.886
+    - type: map_at_100
+      value: 10.040000000000001
+    - type: map_at_1000
+      value: 23.768
+    - type: map_at_3
+      value: 0.674
+    - type: map_at_5
+      value: 1.079
+    - type: mrr_at_1
+      value: 88
+    - type: mrr_at_10
+      value: 93.667
+    - type: mrr_at_100
+      value: 93.667
+    - type: mrr_at_1000
+      value: 93.667
+    - type: mrr_at_3
+      value: 93.667
+    - type: mrr_at_5
+      value: 93.667
+    - type: ndcg_at_1
+      value: 83
+    - type: ndcg_at_10
+      value: 76.777
+    - type: ndcg_at_100
+      value: 55.153
+    - type: ndcg_at_1000
+      value: 47.912
+    - type: ndcg_at_3
+      value: 81.358
+    - type: ndcg_at_5
+      value: 80.74799999999999
+    - type: precision_at_1
+      value: 88
+    - type: precision_at_10
+      value: 80.80000000000001
+    - type: precision_at_100
+      value: 56.02
+    - type: precision_at_1000
+      value: 21.51
+    - type: precision_at_3
+      value: 86
+    - type: precision_at_5
+      value: 86
+    - type: recall_at_1
+      value: 0.243
+    - type: recall_at_10
+      value: 2.0869999999999997
+    - type: recall_at_100
+      value: 13.014000000000001
+    - type: recall_at_1000
+      value: 44.433
+    - type: recall_at_3
+      value: 0.6910000000000001
+    - type: recall_at_5
+      value: 1.1440000000000001
+  - task:
+      type: Retrieval
+    dataset:
+      type: webis-touche2020
+      name: MTEB Touche2020
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 3.066
+    - type: map_at_10
+      value: 10.615
+    - type: map_at_100
+      value: 16.463
+    - type: map_at_1000
+      value: 17.815
+    - type: map_at_3
+      value: 5.7860000000000005
+    - type: map_at_5
+      value: 7.353999999999999
+    - type: mrr_at_1
+      value: 38.775999999999996
+    - type: mrr_at_10
+      value: 53.846000000000004
+    - type: mrr_at_100
+      value: 54.37
+    - type: mrr_at_1000
+      value: 54.37
+    - type: mrr_at_3
+      value: 48.980000000000004
+    - type: mrr_at_5
+      value: 51.735
+    - type: ndcg_at_1
+      value: 34.694
+    - type: ndcg_at_10
+      value: 26.811
+    - type: ndcg_at_100
+      value: 37.342999999999996
+    - type: ndcg_at_1000
+      value: 47.964
+    - type: ndcg_at_3
+      value: 30.906
+    - type: ndcg_at_5
+      value: 27.77
+    - type: precision_at_1
+      value: 38.775999999999996
+    - type: precision_at_10
+      value: 23.878
+    - type: precision_at_100
+      value: 7.632999999999999
+    - type: precision_at_1000
+      value: 1.469
+    - type: precision_at_3
+      value: 31.973000000000003
+    - type: precision_at_5
+      value: 26.939
+    - type: recall_at_1
+      value: 3.066
+    - type: recall_at_10
+      value: 17.112
+    - type: recall_at_100
+      value: 47.723
+    - type: recall_at_1000
+      value: 79.50500000000001
+    - type: recall_at_3
+      value: 6.825
+    - type: recall_at_5
+      value: 9.584
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/toxic_conversations_50k
+      name: MTEB ToxicConversationsClassification
+      config: default
+      split: test
+      revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c
+    metrics:
+    - type: accuracy
+      value: 72.76460000000002
+    - type: ap
+      value: 14.944240012137053
+    - type: f1
+      value: 55.89805777266571
+  - task:
+      type: Classification
+    dataset:
+      type: mteb/tweet_sentiment_extraction
+      name: MTEB TweetSentimentExtractionClassification
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 63.30503678551217
+    - type: f1
+      value: 63.57492701921179
+  - task:
+      type: Clustering
+    dataset:
+      type: mteb/twentynewsgroups-clustering
+      name: MTEB TwentyNewsgroupsClustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 37.51066495006874
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twittersemeval2015-pairclassification
+      name: MTEB TwitterSemEval2015
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 86.07021517553794
+    - type: cos_sim_ap
+      value: 74.15520712370555
+    - type: cos_sim_f1
+      value: 68.64321608040201
+    - type: cos_sim_precision
+      value: 65.51558752997602
+    - type: cos_sim_recall
+      value: 72.0844327176781
+    - type: dot_accuracy
+      value: 80.23484532395541
+    - type: dot_ap
+      value: 54.298763810214176
+    - type: dot_f1
+      value: 53.22254659779924
+    - type: dot_precision
+      value: 46.32525410476936
+    - type: dot_recall
+      value: 62.532981530343015
+    - type: euclidean_accuracy
+      value: 86.04637301066937
+    - type: euclidean_ap
+      value: 73.85333854233123
+    - type: euclidean_f1
+      value: 68.77723660599845
+    - type: euclidean_precision
+      value: 66.87437686939182
+    - type: euclidean_recall
+      value: 70.79155672823218
+    - type: manhattan_accuracy
+      value: 85.98676759849795
+    - type: manhattan_ap
+      value: 73.56016090035973
+    - type: manhattan_f1
+      value: 68.48878539036647
+    - type: manhattan_precision
+      value: 63.9505607690547
+    - type: manhattan_recall
+      value: 73.7203166226913
+    - type: max_accuracy
+      value: 86.07021517553794
+    - type: max_ap
+      value: 74.15520712370555
+    - type: max_f1
+      value: 68.77723660599845
+  - task:
+      type: PairClassification
+    dataset:
+      type: mteb/twitterurlcorpus-pairclassification
+      name: MTEB TwitterURLCorpus
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.92769821865176
+    - type: cos_sim_ap
+      value: 85.78879502899773
+    - type: cos_sim_f1
+      value: 78.14414083990464
+    - type: cos_sim_precision
+      value: 74.61651607480563
+    - type: cos_sim_recall
+      value: 82.0218663381583
+    - type: dot_accuracy
+      value: 84.95750378390964
+    - type: dot_ap
+      value: 75.80219641857563
+    - type: dot_f1
+      value: 70.13966179585681
+    - type: dot_precision
+      value: 65.71140262361251
+    - type: dot_recall
+      value: 75.20788420080073
+    - type: euclidean_accuracy
+      value: 88.93546008460433
+    - type: euclidean_ap
+      value: 85.72056428301667
+    - type: euclidean_f1
+      value: 78.14387902598124
+    - type: euclidean_precision
+      value: 75.3376688344172
+    - type: euclidean_recall
+      value: 81.16723129042192
+    - type: manhattan_accuracy
+      value: 88.96262661543835
+    - type: manhattan_ap
+      value: 85.76605136314335
+    - type: manhattan_f1
+      value: 78.26696165191743
+    - type: manhattan_precision
+      value: 75.0990659496179
+    - type: manhattan_recall
+      value: 81.71388974437943
+    - type: max_accuracy
+      value: 88.96262661543835
+    - type: max_ap
+      value: 85.78879502899773
+    - type: max_f1
+      value: 78.26696165191743
+language:
+- en
+license: mit
+---
+# # Fast-Inference with Ctranslate2
+Speedup inference while reducing memory by 2x-4x using int8 inference in C++ on CPU or GPU.
+
+quantized version of [intfloat/e5-small](https://huggingface.co/intfloat/e5-small)
+```bash
+pip install hf-hub-ctranslate2>=2.10.0 ctranslate2>=3.16.0
+```
+
+```python
+# from transformers import AutoTokenizer
+model_name = "michaelfeil/ct2fast-e5-small"
+
+from hf_hub_ctranslate2 import CT2SentenceTransformer
+model = CT2SentenceTransformer(
+    model_name, compute_type="int8_float16", device="cuda"
+)
+embeddings = model.encode(
+    ["I like soccer", "I like tennis", "The eiffel tower is in Paris"],
+    batch_size=32,
+    convert_to_numpy=True,
+    normalize_embeddings=True,
+)
+print(embeddings.shape, embeddings)
+scores = (embeddings @ embeddings.T) * 100
+
+```
+
+Checkpoint compatible to [ctranslate2>=3.16.0](https://github.com/OpenNMT/CTranslate2)
+and [hf-hub-ctranslate2>=2.10.0](https://github.com/michaelfeil/hf-hub-ctranslate2)
+- `compute_type=int8_float16` for `device="cuda"`
+- `compute_type=int8`  for `device="cpu"`
+
+Converted on 2023-06-18 using
+```
+ct2-transformers-converter --model intfloat/e5-small --output_dir ~/tmp-ct2fast-e5-small --force --copy_files tokenizer.json sentence_bert_config.json README.md modules.json special_tokens_map.json vocab.txt tokenizer_config.json .gitattributes --trust_remote_code
+```
+
+# Licence and other remarks:
+This is just a quantized version. Licence conditions are intended to be idential to original huggingface repo.
+
+# Original description
+    
+
+# E5-small
+
+[Text Embeddings by Weakly-Supervised Contrastive Pre-training](https://arxiv.org/pdf/2212.03533.pdf).
+Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022
+
+This model has 12 layers and the embedding size is 384.
+
+## Usage
+
+Below is an example to encode queries and passages from the MS-MARCO passage ranking dataset.
+
+```python
+import torch.nn.functional as F
+
+from torch import Tensor
+from transformers import AutoTokenizer, AutoModel
+
+
+def average_pool(last_hidden_states: Tensor,
+                 attention_mask: Tensor) -> Tensor:
+    last_hidden = last_hidden_states.masked_fill(~attention_mask[..., None].bool(), 0.0)
+    return last_hidden.sum(dim=1) / attention_mask.sum(dim=1)[..., None]
+
+
+# Each input text should start with "query: " or "passage: ".
+# For tasks other than retrieval, you can simply use the "query: " prefix.
+input_texts = ['query: how much protein should a female eat',
+               'query: summit define',
+               "passage: As a general guideline, the CDC's average requirement of protein for women ages 19 to 70 is 46 grams per day. But, as you can see from this chart, you'll need to increase that if you're expecting or training for a marathon. Check out the chart below to see how much protein you should be eating each day.",
+               "passage: Definition of summit for English Language Learners. : 1  the highest point of a mountain : the top of a mountain. : 2  the highest level. : 3  a meeting or series of meetings between the leaders of two or more governments."]
+
+tokenizer = AutoTokenizer.from_pretrained('intfloat/e5-small')
+model = AutoModel.from_pretrained('intfloat/e5-small')
+
+# Tokenize the input texts
+batch_dict = tokenizer(input_texts, max_length=512, padding=True, truncation=True, return_tensors='pt')
+
+outputs = model(**batch_dict)
+embeddings = average_pool(outputs.last_hidden_state, batch_dict['attention_mask'])
+
+# (Optionally) normalize embeddings
+embeddings = F.normalize(embeddings, p=2, dim=1)
+scores = (embeddings[:2] @ embeddings[2:].T) * 100
+print(scores.tolist())
+```
+
+## Training Details
+
+Please refer to our paper at [https://arxiv.org/pdf/2212.03533.pdf](https://arxiv.org/pdf/2212.03533.pdf).
+
+## Benchmark Evaluation
+
+Check out [unilm/e5](https://github.com/microsoft/unilm/tree/master/e5) to reproduce evaluation results 
+on the [BEIR](https://arxiv.org/abs/2104.08663) and [MTEB benchmark](https://arxiv.org/abs/2210.07316).
+
+## Citation
+
+If you find our paper or models helpful, please consider cite as follows:
+
+```
+@article{wang2022text,
+  title={Text Embeddings by Weakly-Supervised Contrastive Pre-training},
+  author={Wang, Liang and Yang, Nan and Huang, Xiaolong and Jiao, Binxing and Yang, Linjun and Jiang, Daxin and Majumder, Rangan and Wei, Furu},
+  journal={arXiv preprint arXiv:2212.03533},
+  year={2022}
+}
+```
+
+## Limitations
+
+This model only works for English texts. Long texts will be truncated to at most 512 tokens.

config.json

@@ -0,0 +1,6 @@
+{
+  "bos_token": "<s>",
+  "eos_token": "</s>",
+  "layer_norm_epsilon": 1e-12,
+  "unk_token": "[UNK]"
+}

model.bin

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+oid sha256:738ee67946d5969622bf1777a455b1b6eef99d62ce859cd781e1633bcc0b4260
+size 133448364

modules.json

@@ -0,0 +1,20 @@
+[
+    {
+      "idx": 0,
+      "name": "0",
+      "path": "",
+      "type": "sentence_transformers.models.Transformer"
+    },
+    {
+      "idx": 1,
+      "name": "1",
+      "path": "1_Pooling",
+      "type": "sentence_transformers.models.Pooling"
+    },
+    {
+      "idx": 2,
+      "name": "2",
+      "path": "2_Normalize",
+      "type": "sentence_transformers.models.Normalize"
+    }
+  ]

sentence_bert_config.json

@@ -0,0 +1,4 @@
+{
+    "max_seq_length": 512,
+    "do_lower_case": false
+}

special_tokens_map.json

@@ -0,0 +1 @@
+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

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+{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "special_tokens_map_file": null, "name_or_path": "amlt/1109_tnlrv3_bs32k_ft/all_kd_ft", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"}