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+---
+base_model: Snowflake/snowflake-arctic-embed-s
+license: apache-2.0
+pipeline_tag: sentence-similarity
+tags:
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+- mteb
+- arctic
+- snowflake-arctic-embed
+- transformers.js
+- llama-cpp
+- gguf-my-repo
+model-index:
+- name: snowflake-snowflake-arctic-embed-s
+  results:
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonCounterfactualClassification (en)
+      type: mteb/amazon_counterfactual
+      config: en
+      split: test
+      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
+    metrics:
+    - type: accuracy
+      value: 71.17910447761193
+    - type: ap
+      value: 33.15833652904991
+    - type: f1
+      value: 64.86214791591543
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonPolarityClassification
+      type: mteb/amazon_polarity
+      config: default
+      split: test
+      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
+    metrics:
+    - type: accuracy
+      value: 78.750325
+    - type: ap
+      value: 72.83242788470943
+    - type: f1
+      value: 78.63968044029453
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonReviewsClassification (en)
+      type: mteb/amazon_reviews_multi
+      config: en
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 38.264
+    - type: f1
+      value: 37.140269688532825
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB ArguAna
+      type: mteb/arguana
+      config: default
+      split: test
+      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
+    metrics:
+    - type: map_at_1
+      value: 32.646
+    - type: map_at_10
+      value: 48.372
+    - type: map_at_100
+      value: 49.207
+    - type: map_at_1000
+      value: 49.214
+    - type: map_at_3
+      value: 43.611
+    - type: map_at_5
+      value: 46.601
+    - type: mrr_at_1
+      value: 33.144
+    - type: mrr_at_10
+      value: 48.557
+    - type: mrr_at_100
+      value: 49.385
+    - type: mrr_at_1000
+      value: 49.392
+    - type: mrr_at_3
+      value: 43.777
+    - type: mrr_at_5
+      value: 46.792
+    - type: ndcg_at_1
+      value: 32.646
+    - type: ndcg_at_10
+      value: 56.874
+    - type: ndcg_at_100
+      value: 60.307
+    - type: ndcg_at_1000
+      value: 60.465999999999994
+    - type: ndcg_at_3
+      value: 47.339999999999996
+    - type: ndcg_at_5
+      value: 52.685
+    - type: precision_at_1
+      value: 32.646
+    - type: precision_at_10
+      value: 8.378
+    - type: precision_at_100
+      value: 0.984
+    - type: precision_at_1000
+      value: 0.1
+    - type: precision_at_3
+      value: 19.393
+    - type: precision_at_5
+      value: 14.210999999999999
+    - type: recall_at_1
+      value: 32.646
+    - type: recall_at_10
+      value: 83.784
+    - type: recall_at_100
+      value: 98.43499999999999
+    - type: recall_at_1000
+      value: 99.644
+    - type: recall_at_3
+      value: 58.179
+    - type: recall_at_5
+      value: 71.053
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ArxivClusteringP2P
+      type: mteb/arxiv-clustering-p2p
+      config: default
+      split: test
+      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
+    metrics:
+    - type: v_measure
+      value: 44.94353025039141
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ArxivClusteringS2S
+      type: mteb/arxiv-clustering-s2s
+      config: default
+      split: test
+      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
+    metrics:
+    - type: v_measure
+      value: 35.870836103029156
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB AskUbuntuDupQuestions
+      type: mteb/askubuntudupquestions-reranking
+      config: default
+      split: test
+      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
+    metrics:
+    - type: map
+      value: 61.149290266979236
+    - type: mrr
+      value: 73.8448093919008
+  - task:
+      type: STS
+    dataset:
+      name: MTEB BIOSSES
+      type: mteb/biosses-sts
+      config: default
+      split: test
+      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
+    metrics:
+    - type: cos_sim_pearson
+      value: 87.055571064151
+    - type: cos_sim_spearman
+      value: 86.2652186235749
+    - type: euclidean_pearson
+      value: 85.82039272282503
+    - type: euclidean_spearman
+      value: 86.2652186235749
+    - type: manhattan_pearson
+      value: 85.95825392094812
+    - type: manhattan_spearman
+      value: 86.6742640885316
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB Banking77Classification
+      type: mteb/banking77
+      config: default
+      split: test
+      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
+    metrics:
+    - type: accuracy
+      value: 79.11688311688312
+    - type: f1
+      value: 78.28328901613885
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB BigPatentClustering
+      type: jinaai/big-patent-clustering
+      config: default
+      split: test
+      revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
+    metrics:
+    - type: v_measure
+      value: 19.147523589859325
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB BiorxivClusteringP2P
+      type: mteb/biorxiv-clustering-p2p
+      config: default
+      split: test
+      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
+    metrics:
+    - type: v_measure
+      value: 35.68369864124274
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB BiorxivClusteringS2S
+      type: mteb/biorxiv-clustering-s2s
+      config: default
+      split: test
+      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
+    metrics:
+    - type: v_measure
+      value: 30.474958792950872
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackAndroidRetrieval
+      type: mteb/cqadupstack-android
+      config: default
+      split: test
+      revision: f46a197baaae43b4f621051089b82a364682dfeb
+    metrics:
+    - type: map_at_1
+      value: 33.183
+    - type: map_at_10
+      value: 43.989
+    - type: map_at_100
+      value: 45.389
+    - type: map_at_1000
+      value: 45.517
+    - type: map_at_3
+      value: 40.275
+    - type: map_at_5
+      value: 42.306
+    - type: mrr_at_1
+      value: 40.486
+    - type: mrr_at_10
+      value: 49.62
+    - type: mrr_at_100
+      value: 50.351
+    - type: mrr_at_1000
+      value: 50.393
+    - type: mrr_at_3
+      value: 46.805
+    - type: mrr_at_5
+      value: 48.429
+    - type: ndcg_at_1
+      value: 40.486
+    - type: ndcg_at_10
+      value: 50.249
+    - type: ndcg_at_100
+      value: 55.206
+    - type: ndcg_at_1000
+      value: 57.145
+    - type: ndcg_at_3
+      value: 44.852
+    - type: ndcg_at_5
+      value: 47.355000000000004
+    - type: precision_at_1
+      value: 40.486
+    - type: precision_at_10
+      value: 9.571
+    - type: precision_at_100
+      value: 1.4949999999999999
+    - type: precision_at_1000
+      value: 0.196
+    - type: precision_at_3
+      value: 21.173000000000002
+    - type: precision_at_5
+      value: 15.622
+    - type: recall_at_1
+      value: 33.183
+    - type: recall_at_10
+      value: 62.134
+    - type: recall_at_100
+      value: 82.73
+    - type: recall_at_1000
+      value: 94.93599999999999
+    - type: recall_at_3
+      value: 46.497
+    - type: recall_at_5
+      value: 53.199
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackEnglishRetrieval
+      type: mteb/cqadupstack-english
+      config: default
+      split: test
+      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
+    metrics:
+    - type: map_at_1
+      value: 32.862
+    - type: map_at_10
+      value: 42.439
+    - type: map_at_100
+      value: 43.736999999999995
+    - type: map_at_1000
+      value: 43.864
+    - type: map_at_3
+      value: 39.67
+    - type: map_at_5
+      value: 41.202
+    - type: mrr_at_1
+      value: 40.892
+    - type: mrr_at_10
+      value: 48.61
+    - type: mrr_at_100
+      value: 49.29
+    - type: mrr_at_1000
+      value: 49.332
+    - type: mrr_at_3
+      value: 46.688
+    - type: mrr_at_5
+      value: 47.803000000000004
+    - type: ndcg_at_1
+      value: 40.892
+    - type: ndcg_at_10
+      value: 47.797
+    - type: ndcg_at_100
+      value: 52.17699999999999
+    - type: ndcg_at_1000
+      value: 54.127
+    - type: ndcg_at_3
+      value: 44.189
+    - type: ndcg_at_5
+      value: 45.821
+    - type: precision_at_1
+      value: 40.892
+    - type: precision_at_10
+      value: 8.841000000000001
+    - type: precision_at_100
+      value: 1.419
+    - type: precision_at_1000
+      value: 0.188
+    - type: precision_at_3
+      value: 21.104
+    - type: precision_at_5
+      value: 14.777000000000001
+    - type: recall_at_1
+      value: 32.862
+    - type: recall_at_10
+      value: 56.352999999999994
+    - type: recall_at_100
+      value: 74.795
+    - type: recall_at_1000
+      value: 86.957
+    - type: recall_at_3
+      value: 45.269999999999996
+    - type: recall_at_5
+      value: 50.053000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackGamingRetrieval
+      type: mteb/cqadupstack-gaming
+      config: default
+      split: test
+      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
+    metrics:
+    - type: map_at_1
+      value: 42.998999999999995
+    - type: map_at_10
+      value: 54.745
+    - type: map_at_100
+      value: 55.650999999999996
+    - type: map_at_1000
+      value: 55.703
+    - type: map_at_3
+      value: 51.67
+    - type: map_at_5
+      value: 53.503
+    - type: mrr_at_1
+      value: 49.028
+    - type: mrr_at_10
+      value: 58.172000000000004
+    - type: mrr_at_100
+      value: 58.744
+    - type: mrr_at_1000
+      value: 58.769000000000005
+    - type: mrr_at_3
+      value: 55.977
+    - type: mrr_at_5
+      value: 57.38799999999999
+    - type: ndcg_at_1
+      value: 49.028
+    - type: ndcg_at_10
+      value: 60.161
+    - type: ndcg_at_100
+      value: 63.806
+    - type: ndcg_at_1000
+      value: 64.821
+    - type: ndcg_at_3
+      value: 55.199
+    - type: ndcg_at_5
+      value: 57.830999999999996
+    - type: precision_at_1
+      value: 49.028
+    - type: precision_at_10
+      value: 9.455
+    - type: precision_at_100
+      value: 1.216
+    - type: precision_at_1000
+      value: 0.135
+    - type: precision_at_3
+      value: 24.242
+    - type: precision_at_5
+      value: 16.614
+    - type: recall_at_1
+      value: 42.998999999999995
+    - type: recall_at_10
+      value: 72.542
+    - type: recall_at_100
+      value: 88.605
+    - type: recall_at_1000
+      value: 95.676
+    - type: recall_at_3
+      value: 59.480999999999995
+    - type: recall_at_5
+      value: 65.886
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackGisRetrieval
+      type: mteb/cqadupstack-gis
+      config: default
+      split: test
+      revision: 5003b3064772da1887988e05400cf3806fe491f2
+    metrics:
+    - type: map_at_1
+      value: 27.907
+    - type: map_at_10
+      value: 35.975
+    - type: map_at_100
+      value: 36.985
+    - type: map_at_1000
+      value: 37.063
+    - type: map_at_3
+      value: 33.467999999999996
+    - type: map_at_5
+      value: 34.749
+    - type: mrr_at_1
+      value: 30.056
+    - type: mrr_at_10
+      value: 38.047
+    - type: mrr_at_100
+      value: 38.932
+    - type: mrr_at_1000
+      value: 38.991
+    - type: mrr_at_3
+      value: 35.705999999999996
+    - type: mrr_at_5
+      value: 36.966
+    - type: ndcg_at_1
+      value: 30.056
+    - type: ndcg_at_10
+      value: 40.631
+    - type: ndcg_at_100
+      value: 45.564
+    - type: ndcg_at_1000
+      value: 47.685
+    - type: ndcg_at_3
+      value: 35.748000000000005
+    - type: ndcg_at_5
+      value: 37.921
+    - type: precision_at_1
+      value: 30.056
+    - type: precision_at_10
+      value: 6.079
+    - type: precision_at_100
+      value: 0.898
+    - type: precision_at_1000
+      value: 0.11199999999999999
+    - type: precision_at_3
+      value: 14.727
+    - type: precision_at_5
+      value: 10.056
+    - type: recall_at_1
+      value: 27.907
+    - type: recall_at_10
+      value: 52.981
+    - type: recall_at_100
+      value: 75.53999999999999
+    - type: recall_at_1000
+      value: 91.759
+    - type: recall_at_3
+      value: 39.878
+    - type: recall_at_5
+      value: 45.077
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackMathematicaRetrieval
+      type: mteb/cqadupstack-mathematica
+      config: default
+      split: test
+      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
+    metrics:
+    - type: map_at_1
+      value: 16.764000000000003
+    - type: map_at_10
+      value: 24.294
+    - type: map_at_100
+      value: 25.507999999999996
+    - type: map_at_1000
+      value: 25.64
+    - type: map_at_3
+      value: 21.807000000000002
+    - type: map_at_5
+      value: 23.21
+    - type: mrr_at_1
+      value: 20.771
+    - type: mrr_at_10
+      value: 28.677000000000003
+    - type: mrr_at_100
+      value: 29.742
+    - type: mrr_at_1000
+      value: 29.816
+    - type: mrr_at_3
+      value: 26.327
+    - type: mrr_at_5
+      value: 27.639000000000003
+    - type: ndcg_at_1
+      value: 20.771
+    - type: ndcg_at_10
+      value: 29.21
+    - type: ndcg_at_100
+      value: 34.788000000000004
+    - type: ndcg_at_1000
+      value: 37.813
+    - type: ndcg_at_3
+      value: 24.632
+    - type: ndcg_at_5
+      value: 26.801000000000002
+    - type: precision_at_1
+      value: 20.771
+    - type: precision_at_10
+      value: 5.373
+    - type: precision_at_100
+      value: 0.923
+    - type: precision_at_1000
+      value: 0.133
+    - type: precision_at_3
+      value: 12.065
+    - type: precision_at_5
+      value: 8.706
+    - type: recall_at_1
+      value: 16.764000000000003
+    - type: recall_at_10
+      value: 40.072
+    - type: recall_at_100
+      value: 63.856
+    - type: recall_at_1000
+      value: 85.141
+    - type: recall_at_3
+      value: 27.308
+    - type: recall_at_5
+      value: 32.876
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackPhysicsRetrieval
+      type: mteb/cqadupstack-physics
+      config: default
+      split: test
+      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
+    metrics:
+    - type: map_at_1
+      value: 31.194
+    - type: map_at_10
+      value: 40.731
+    - type: map_at_100
+      value: 42.073
+    - type: map_at_1000
+      value: 42.178
+    - type: map_at_3
+      value: 37.726
+    - type: map_at_5
+      value: 39.474
+    - type: mrr_at_1
+      value: 37.729
+    - type: mrr_at_10
+      value: 46.494
+    - type: mrr_at_100
+      value: 47.368
+    - type: mrr_at_1000
+      value: 47.407
+    - type: mrr_at_3
+      value: 44.224999999999994
+    - type: mrr_at_5
+      value: 45.582
+    - type: ndcg_at_1
+      value: 37.729
+    - type: ndcg_at_10
+      value: 46.312999999999995
+    - type: ndcg_at_100
+      value: 51.915
+    - type: ndcg_at_1000
+      value: 53.788000000000004
+    - type: ndcg_at_3
+      value: 41.695
+    - type: ndcg_at_5
+      value: 43.956
+    - type: precision_at_1
+      value: 37.729
+    - type: precision_at_10
+      value: 8.181
+    - type: precision_at_100
+      value: 1.275
+    - type: precision_at_1000
+      value: 0.16199999999999998
+    - type: precision_at_3
+      value: 19.41
+    - type: precision_at_5
+      value: 13.648
+    - type: recall_at_1
+      value: 31.194
+    - type: recall_at_10
+      value: 57.118
+    - type: recall_at_100
+      value: 80.759
+    - type: recall_at_1000
+      value: 92.779
+    - type: recall_at_3
+      value: 44.083
+    - type: recall_at_5
+      value: 50.044999999999995
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackProgrammersRetrieval
+      type: mteb/cqadupstack-programmers
+      config: default
+      split: test
+      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
+    metrics:
+    - type: map_at_1
+      value: 28.047
+    - type: map_at_10
+      value: 37.79
+    - type: map_at_100
+      value: 39.145
+    - type: map_at_1000
+      value: 39.254
+    - type: map_at_3
+      value: 34.857
+    - type: map_at_5
+      value: 36.545
+    - type: mrr_at_1
+      value: 35.388
+    - type: mrr_at_10
+      value: 43.475
+    - type: mrr_at_100
+      value: 44.440000000000005
+    - type: mrr_at_1000
+      value: 44.494
+    - type: mrr_at_3
+      value: 41.286
+    - type: mrr_at_5
+      value: 42.673
+    - type: ndcg_at_1
+      value: 35.388
+    - type: ndcg_at_10
+      value: 43.169000000000004
+    - type: ndcg_at_100
+      value: 48.785000000000004
+    - type: ndcg_at_1000
+      value: 51.029
+    - type: ndcg_at_3
+      value: 38.801
+    - type: ndcg_at_5
+      value: 40.9
+    - type: precision_at_1
+      value: 35.388
+    - type: precision_at_10
+      value: 7.7509999999999994
+    - type: precision_at_100
+      value: 1.212
+    - type: precision_at_1000
+      value: 0.157
+    - type: precision_at_3
+      value: 18.455
+    - type: precision_at_5
+      value: 13.014000000000001
+    - type: recall_at_1
+      value: 28.047
+    - type: recall_at_10
+      value: 53.53099999999999
+    - type: recall_at_100
+      value: 77.285
+    - type: recall_at_1000
+      value: 92.575
+    - type: recall_at_3
+      value: 40.949000000000005
+    - type: recall_at_5
+      value: 46.742
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackRetrieval
+      type: mteb/cqadupstack
+      config: default
+      split: test
+      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
+    metrics:
+    - type: map_at_1
+      value: 28.131999999999994
+    - type: map_at_10
+      value: 36.93333333333334
+    - type: map_at_100
+      value: 38.117250000000006
+    - type: map_at_1000
+      value: 38.23275
+    - type: map_at_3
+      value: 34.19708333333333
+    - type: map_at_5
+      value: 35.725166666666674
+    - type: mrr_at_1
+      value: 33.16116666666667
+    - type: mrr_at_10
+      value: 41.057833333333335
+    - type: mrr_at_100
+      value: 41.90033333333333
+    - type: mrr_at_1000
+      value: 41.95625
+    - type: mrr_at_3
+      value: 38.757333333333335
+    - type: mrr_at_5
+      value: 40.097333333333324
+    - type: ndcg_at_1
+      value: 33.16116666666667
+    - type: ndcg_at_10
+      value: 42.01983333333333
+    - type: ndcg_at_100
+      value: 46.99916666666667
+    - type: ndcg_at_1000
+      value: 49.21783333333334
+    - type: ndcg_at_3
+      value: 37.479916666666654
+    - type: ndcg_at_5
+      value: 39.6355
+    - type: precision_at_1
+      value: 33.16116666666667
+    - type: precision_at_10
+      value: 7.230249999999999
+    - type: precision_at_100
+      value: 1.1411666666666667
+    - type: precision_at_1000
+      value: 0.1520833333333333
+    - type: precision_at_3
+      value: 17.028166666666667
+    - type: precision_at_5
+      value: 12.046999999999999
+    - type: recall_at_1
+      value: 28.131999999999994
+    - type: recall_at_10
+      value: 52.825500000000005
+    - type: recall_at_100
+      value: 74.59608333333333
+    - type: recall_at_1000
+      value: 89.87916666666668
+    - type: recall_at_3
+      value: 40.13625
+    - type: recall_at_5
+      value: 45.699999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackStatsRetrieval
+      type: mteb/cqadupstack-stats
+      config: default
+      split: test
+      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
+    metrics:
+    - type: map_at_1
+      value: 24.773999999999997
+    - type: map_at_10
+      value: 31.997999999999998
+    - type: map_at_100
+      value: 32.857
+    - type: map_at_1000
+      value: 32.957
+    - type: map_at_3
+      value: 30.041
+    - type: map_at_5
+      value: 31.119000000000003
+    - type: mrr_at_1
+      value: 27.607
+    - type: mrr_at_10
+      value: 34.538000000000004
+    - type: mrr_at_100
+      value: 35.308
+    - type: mrr_at_1000
+      value: 35.375
+    - type: mrr_at_3
+      value: 32.643
+    - type: mrr_at_5
+      value: 33.755
+    - type: ndcg_at_1
+      value: 27.607
+    - type: ndcg_at_10
+      value: 36.035000000000004
+    - type: ndcg_at_100
+      value: 40.351
+    - type: ndcg_at_1000
+      value: 42.684
+    - type: ndcg_at_3
+      value: 32.414
+    - type: ndcg_at_5
+      value: 34.11
+    - type: precision_at_1
+      value: 27.607
+    - type: precision_at_10
+      value: 5.6129999999999995
+    - type: precision_at_100
+      value: 0.8370000000000001
+    - type: precision_at_1000
+      value: 0.11199999999999999
+    - type: precision_at_3
+      value: 13.957
+    - type: precision_at_5
+      value: 9.571
+    - type: recall_at_1
+      value: 24.773999999999997
+    - type: recall_at_10
+      value: 45.717
+    - type: recall_at_100
+      value: 65.499
+    - type: recall_at_1000
+      value: 82.311
+    - type: recall_at_3
+      value: 35.716
+    - type: recall_at_5
+      value: 40.007999999999996
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackTexRetrieval
+      type: mteb/cqadupstack-tex
+      config: default
+      split: test
+      revision: 46989137a86843e03a6195de44b09deda022eec7
+    metrics:
+    - type: map_at_1
+      value: 19.227
+    - type: map_at_10
+      value: 26.649
+    - type: map_at_100
+      value: 27.711999999999996
+    - type: map_at_1000
+      value: 27.837
+    - type: map_at_3
+      value: 24.454
+    - type: map_at_5
+      value: 25.772000000000002
+    - type: mrr_at_1
+      value: 23.433999999999997
+    - type: mrr_at_10
+      value: 30.564999999999998
+    - type: mrr_at_100
+      value: 31.44
+    - type: mrr_at_1000
+      value: 31.513999999999996
+    - type: mrr_at_3
+      value: 28.435
+    - type: mrr_at_5
+      value: 29.744999999999997
+    - type: ndcg_at_1
+      value: 23.433999999999997
+    - type: ndcg_at_10
+      value: 31.104
+    - type: ndcg_at_100
+      value: 36.172
+    - type: ndcg_at_1000
+      value: 39.006
+    - type: ndcg_at_3
+      value: 27.248
+    - type: ndcg_at_5
+      value: 29.249000000000002
+    - type: precision_at_1
+      value: 23.433999999999997
+    - type: precision_at_10
+      value: 5.496
+    - type: precision_at_100
+      value: 0.9490000000000001
+    - type: precision_at_1000
+      value: 0.13699999999999998
+    - type: precision_at_3
+      value: 12.709000000000001
+    - type: precision_at_5
+      value: 9.209
+    - type: recall_at_1
+      value: 19.227
+    - type: recall_at_10
+      value: 40.492
+    - type: recall_at_100
+      value: 63.304
+    - type: recall_at_1000
+      value: 83.45
+    - type: recall_at_3
+      value: 29.713
+    - type: recall_at_5
+      value: 34.82
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackUnixRetrieval
+      type: mteb/cqadupstack-unix
+      config: default
+      split: test
+      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
+    metrics:
+    - type: map_at_1
+      value: 29.199
+    - type: map_at_10
+      value: 37.617
+    - type: map_at_100
+      value: 38.746
+    - type: map_at_1000
+      value: 38.851
+    - type: map_at_3
+      value: 34.882000000000005
+    - type: map_at_5
+      value: 36.571999999999996
+    - type: mrr_at_1
+      value: 33.489000000000004
+    - type: mrr_at_10
+      value: 41.089999999999996
+    - type: mrr_at_100
+      value: 41.965
+    - type: mrr_at_1000
+      value: 42.028
+    - type: mrr_at_3
+      value: 38.666
+    - type: mrr_at_5
+      value: 40.159
+    - type: ndcg_at_1
+      value: 33.489000000000004
+    - type: ndcg_at_10
+      value: 42.487
+    - type: ndcg_at_100
+      value: 47.552
+    - type: ndcg_at_1000
+      value: 49.774
+    - type: ndcg_at_3
+      value: 37.623
+    - type: ndcg_at_5
+      value: 40.184999999999995
+    - type: precision_at_1
+      value: 33.489000000000004
+    - type: precision_at_10
+      value: 6.94
+    - type: precision_at_100
+      value: 1.0699999999999998
+    - type: precision_at_1000
+      value: 0.136
+    - type: precision_at_3
+      value: 16.667
+    - type: precision_at_5
+      value: 11.922
+    - type: recall_at_1
+      value: 29.199
+    - type: recall_at_10
+      value: 53.689
+    - type: recall_at_100
+      value: 75.374
+    - type: recall_at_1000
+      value: 90.64999999999999
+    - type: recall_at_3
+      value: 40.577999999999996
+    - type: recall_at_5
+      value: 46.909
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackWebmastersRetrieval
+      type: mteb/cqadupstack-webmasters
+      config: default
+      split: test
+      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
+    metrics:
+    - type: map_at_1
+      value: 27.206999999999997
+    - type: map_at_10
+      value: 36.146
+    - type: map_at_100
+      value: 37.759
+    - type: map_at_1000
+      value: 37.979
+    - type: map_at_3
+      value: 32.967999999999996
+    - type: map_at_5
+      value: 34.809
+    - type: mrr_at_1
+      value: 32.806000000000004
+    - type: mrr_at_10
+      value: 40.449
+    - type: mrr_at_100
+      value: 41.404999999999994
+    - type: mrr_at_1000
+      value: 41.457
+    - type: mrr_at_3
+      value: 37.614999999999995
+    - type: mrr_at_5
+      value: 39.324999999999996
+    - type: ndcg_at_1
+      value: 32.806000000000004
+    - type: ndcg_at_10
+      value: 41.911
+    - type: ndcg_at_100
+      value: 47.576
+    - type: ndcg_at_1000
+      value: 50.072
+    - type: ndcg_at_3
+      value: 36.849
+    - type: ndcg_at_5
+      value: 39.475
+    - type: precision_at_1
+      value: 32.806000000000004
+    - type: precision_at_10
+      value: 8.103
+    - type: precision_at_100
+      value: 1.557
+    - type: precision_at_1000
+      value: 0.242
+    - type: precision_at_3
+      value: 17.26
+    - type: precision_at_5
+      value: 12.885
+    - type: recall_at_1
+      value: 27.206999999999997
+    - type: recall_at_10
+      value: 52.56999999999999
+    - type: recall_at_100
+      value: 78.302
+    - type: recall_at_1000
+      value: 94.121
+    - type: recall_at_3
+      value: 38.317
+    - type: recall_at_5
+      value: 45.410000000000004
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CQADupstackWordpressRetrieval
+      type: mteb/cqadupstack-wordpress
+      config: default
+      split: test
+      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
+    metrics:
+    - type: map_at_1
+      value: 24.221
+    - type: map_at_10
+      value: 30.826999999999998
+    - type: map_at_100
+      value: 31.845000000000002
+    - type: map_at_1000
+      value: 31.95
+    - type: map_at_3
+      value: 28.547
+    - type: map_at_5
+      value: 29.441
+    - type: mrr_at_1
+      value: 26.247999999999998
+    - type: mrr_at_10
+      value: 32.957
+    - type: mrr_at_100
+      value: 33.819
+    - type: mrr_at_1000
+      value: 33.899
+    - type: mrr_at_3
+      value: 30.714999999999996
+    - type: mrr_at_5
+      value: 31.704
+    - type: ndcg_at_1
+      value: 26.247999999999998
+    - type: ndcg_at_10
+      value: 35.171
+    - type: ndcg_at_100
+      value: 40.098
+    - type: ndcg_at_1000
+      value: 42.67
+    - type: ndcg_at_3
+      value: 30.508999999999997
+    - type: ndcg_at_5
+      value: 32.022
+    - type: precision_at_1
+      value: 26.247999999999998
+    - type: precision_at_10
+      value: 5.36
+    - type: precision_at_100
+      value: 0.843
+    - type: precision_at_1000
+      value: 0.11499999999999999
+    - type: precision_at_3
+      value: 12.568999999999999
+    - type: precision_at_5
+      value: 8.540000000000001
+    - type: recall_at_1
+      value: 24.221
+    - type: recall_at_10
+      value: 46.707
+    - type: recall_at_100
+      value: 69.104
+    - type: recall_at_1000
+      value: 88.19500000000001
+    - type: recall_at_3
+      value: 33.845
+    - type: recall_at_5
+      value: 37.375
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB ClimateFEVER
+      type: mteb/climate-fever
+      config: default
+      split: test
+      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
+    metrics:
+    - type: map_at_1
+      value: 13.624
+    - type: map_at_10
+      value: 22.557
+    - type: map_at_100
+      value: 24.367
+    - type: map_at_1000
+      value: 24.54
+    - type: map_at_3
+      value: 18.988
+    - type: map_at_5
+      value: 20.785999999999998
+    - type: mrr_at_1
+      value: 30.619000000000003
+    - type: mrr_at_10
+      value: 42.019
+    - type: mrr_at_100
+      value: 42.818
+    - type: mrr_at_1000
+      value: 42.856
+    - type: mrr_at_3
+      value: 38.578
+    - type: mrr_at_5
+      value: 40.669
+    - type: ndcg_at_1
+      value: 30.619000000000003
+    - type: ndcg_at_10
+      value: 31.252999999999997
+    - type: ndcg_at_100
+      value: 38.238
+    - type: ndcg_at_1000
+      value: 41.368
+    - type: ndcg_at_3
+      value: 25.843
+    - type: ndcg_at_5
+      value: 27.638
+    - type: precision_at_1
+      value: 30.619000000000003
+    - type: precision_at_10
+      value: 9.687
+    - type: precision_at_100
+      value: 1.718
+    - type: precision_at_1000
+      value: 0.22999999999999998
+    - type: precision_at_3
+      value: 18.849
+    - type: precision_at_5
+      value: 14.463000000000001
+    - type: recall_at_1
+      value: 13.624
+    - type: recall_at_10
+      value: 36.693999999999996
+    - type: recall_at_100
+      value: 60.9
+    - type: recall_at_1000
+      value: 78.46
+    - type: recall_at_3
+      value: 23.354
+    - type: recall_at_5
+      value: 28.756999999999998
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB DBPedia
+      type: mteb/dbpedia
+      config: default
+      split: test
+      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
+    metrics:
+    - type: map_at_1
+      value: 9.077
+    - type: map_at_10
+      value: 19.813
+    - type: map_at_100
+      value: 27.822999999999997
+    - type: map_at_1000
+      value: 29.485
+    - type: map_at_3
+      value: 14.255999999999998
+    - type: map_at_5
+      value: 16.836000000000002
+    - type: mrr_at_1
+      value: 69.25
+    - type: mrr_at_10
+      value: 77.059
+    - type: mrr_at_100
+      value: 77.41
+    - type: mrr_at_1000
+      value: 77.416
+    - type: mrr_at_3
+      value: 75.625
+    - type: mrr_at_5
+      value: 76.512
+    - type: ndcg_at_1
+      value: 55.75
+    - type: ndcg_at_10
+      value: 41.587
+    - type: ndcg_at_100
+      value: 46.048
+    - type: ndcg_at_1000
+      value: 53.172
+    - type: ndcg_at_3
+      value: 46.203
+    - type: ndcg_at_5
+      value: 43.696
+    - type: precision_at_1
+      value: 69.25
+    - type: precision_at_10
+      value: 32.95
+    - type: precision_at_100
+      value: 10.555
+    - type: precision_at_1000
+      value: 2.136
+    - type: precision_at_3
+      value: 49.667
+    - type: precision_at_5
+      value: 42.5
+    - type: recall_at_1
+      value: 9.077
+    - type: recall_at_10
+      value: 25.249
+    - type: recall_at_100
+      value: 51.964
+    - type: recall_at_1000
+      value: 74.51
+    - type: recall_at_3
+      value: 15.584000000000001
+    - type: recall_at_5
+      value: 19.717000000000002
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB EmotionClassification
+      type: mteb/emotion
+      config: default
+      split: test
+      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
+    metrics:
+    - type: accuracy
+      value: 45.769999999999996
+    - type: f1
+      value: 41.64144711933962
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB FEVER
+      type: mteb/fever
+      config: default
+      split: test
+      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
+    metrics:
+    - type: map_at_1
+      value: 67.098
+    - type: map_at_10
+      value: 77.69800000000001
+    - type: map_at_100
+      value: 77.947
+    - type: map_at_1000
+      value: 77.961
+    - type: map_at_3
+      value: 76.278
+    - type: map_at_5
+      value: 77.217
+    - type: mrr_at_1
+      value: 72.532
+    - type: mrr_at_10
+      value: 82.41199999999999
+    - type: mrr_at_100
+      value: 82.527
+    - type: mrr_at_1000
+      value: 82.529
+    - type: mrr_at_3
+      value: 81.313
+    - type: mrr_at_5
+      value: 82.069
+    - type: ndcg_at_1
+      value: 72.532
+    - type: ndcg_at_10
+      value: 82.488
+    - type: ndcg_at_100
+      value: 83.382
+    - type: ndcg_at_1000
+      value: 83.622
+    - type: ndcg_at_3
+      value: 80.101
+    - type: ndcg_at_5
+      value: 81.52199999999999
+    - type: precision_at_1
+      value: 72.532
+    - type: precision_at_10
+      value: 10.203
+    - type: precision_at_100
+      value: 1.082
+    - type: precision_at_1000
+      value: 0.11199999999999999
+    - type: precision_at_3
+      value: 31.308000000000003
+    - type: precision_at_5
+      value: 19.652
+    - type: recall_at_1
+      value: 67.098
+    - type: recall_at_10
+      value: 92.511
+    - type: recall_at_100
+      value: 96.06099999999999
+    - type: recall_at_1000
+      value: 97.548
+    - type: recall_at_3
+      value: 86.105
+    - type: recall_at_5
+      value: 89.661
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB FiQA2018
+      type: mteb/fiqa
+      config: default
+      split: test
+      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
+    metrics:
+    - type: map_at_1
+      value: 18.681
+    - type: map_at_10
+      value: 31.739
+    - type: map_at_100
+      value: 33.503
+    - type: map_at_1000
+      value: 33.69
+    - type: map_at_3
+      value: 27.604
+    - type: map_at_5
+      value: 29.993
+    - type: mrr_at_1
+      value: 37.5
+    - type: mrr_at_10
+      value: 46.933
+    - type: mrr_at_100
+      value: 47.771
+    - type: mrr_at_1000
+      value: 47.805
+    - type: mrr_at_3
+      value: 44.239
+    - type: mrr_at_5
+      value: 45.766
+    - type: ndcg_at_1
+      value: 37.5
+    - type: ndcg_at_10
+      value: 39.682
+    - type: ndcg_at_100
+      value: 46.127
+    - type: ndcg_at_1000
+      value: 48.994
+    - type: ndcg_at_3
+      value: 35.655
+    - type: ndcg_at_5
+      value: 37.036
+    - type: precision_at_1
+      value: 37.5
+    - type: precision_at_10
+      value: 11.08
+    - type: precision_at_100
+      value: 1.765
+    - type: precision_at_1000
+      value: 0.22999999999999998
+    - type: precision_at_3
+      value: 23.919999999999998
+    - type: precision_at_5
+      value: 17.809
+    - type: recall_at_1
+      value: 18.681
+    - type: recall_at_10
+      value: 47.548
+    - type: recall_at_100
+      value: 71.407
+    - type: recall_at_1000
+      value: 87.805
+    - type: recall_at_3
+      value: 32.979
+    - type: recall_at_5
+      value: 39.192
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB HotpotQA
+      type: mteb/hotpotqa
+      config: default
+      split: test
+      revision: ab518f4d6fcca38d87c25209f94beba119d02014
+    metrics:
+    - type: map_at_1
+      value: 38.257999999999996
+    - type: map_at_10
+      value: 57.605
+    - type: map_at_100
+      value: 58.50300000000001
+    - type: map_at_1000
+      value: 58.568
+    - type: map_at_3
+      value: 54.172
+    - type: map_at_5
+      value: 56.323
+    - type: mrr_at_1
+      value: 76.51599999999999
+    - type: mrr_at_10
+      value: 82.584
+    - type: mrr_at_100
+      value: 82.78
+    - type: mrr_at_1000
+      value: 82.787
+    - type: mrr_at_3
+      value: 81.501
+    - type: mrr_at_5
+      value: 82.185
+    - type: ndcg_at_1
+      value: 76.51599999999999
+    - type: ndcg_at_10
+      value: 66.593
+    - type: ndcg_at_100
+      value: 69.699
+    - type: ndcg_at_1000
+      value: 70.953
+    - type: ndcg_at_3
+      value: 61.673
+    - type: ndcg_at_5
+      value: 64.42
+    - type: precision_at_1
+      value: 76.51599999999999
+    - type: precision_at_10
+      value: 13.857
+    - type: precision_at_100
+      value: 1.628
+    - type: precision_at_1000
+      value: 0.179
+    - type: precision_at_3
+      value: 38.956
+    - type: precision_at_5
+      value: 25.541999999999998
+    - type: recall_at_1
+      value: 38.257999999999996
+    - type: recall_at_10
+      value: 69.284
+    - type: recall_at_100
+      value: 81.391
+    - type: recall_at_1000
+      value: 89.689
+    - type: recall_at_3
+      value: 58.433
+    - type: recall_at_5
+      value: 63.856
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB ImdbClassification
+      type: mteb/imdb
+      config: default
+      split: test
+      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
+    metrics:
+    - type: accuracy
+      value: 69.48679999999999
+    - type: ap
+      value: 63.97638838971138
+    - type: f1
+      value: 69.22731638841675
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MSMARCO
+      type: mteb/msmarco
+      config: default
+      split: dev
+      revision: c5a29a104738b98a9e76336939199e264163d4a0
+    metrics:
+    - type: map_at_1
+      value: 20.916999999999998
+    - type: map_at_10
+      value: 32.929
+    - type: map_at_100
+      value: 34.1
+    - type: map_at_1000
+      value: 34.152
+    - type: map_at_3
+      value: 29.065
+    - type: map_at_5
+      value: 31.287
+    - type: mrr_at_1
+      value: 21.562
+    - type: mrr_at_10
+      value: 33.533
+    - type: mrr_at_100
+      value: 34.644000000000005
+    - type: mrr_at_1000
+      value: 34.69
+    - type: mrr_at_3
+      value: 29.735
+    - type: mrr_at_5
+      value: 31.928
+    - type: ndcg_at_1
+      value: 21.562
+    - type: ndcg_at_10
+      value: 39.788000000000004
+    - type: ndcg_at_100
+      value: 45.434999999999995
+    - type: ndcg_at_1000
+      value: 46.75
+    - type: ndcg_at_3
+      value: 31.942999999999998
+    - type: ndcg_at_5
+      value: 35.888
+    - type: precision_at_1
+      value: 21.562
+    - type: precision_at_10
+      value: 6.348
+    - type: precision_at_100
+      value: 0.918
+    - type: precision_at_1000
+      value: 0.10300000000000001
+    - type: precision_at_3
+      value: 13.682
+    - type: precision_at_5
+      value: 10.189
+    - type: recall_at_1
+      value: 20.916999999999998
+    - type: recall_at_10
+      value: 60.926
+    - type: recall_at_100
+      value: 87.03800000000001
+    - type: recall_at_1000
+      value: 97.085
+    - type: recall_at_3
+      value: 39.637
+    - type: recall_at_5
+      value: 49.069
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MTOPDomainClassification (en)
+      type: mteb/mtop_domain
+      config: en
+      split: test
+      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
+    metrics:
+    - type: accuracy
+      value: 90.93935248518011
+    - type: f1
+      value: 90.56439321844506
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MTOPIntentClassification (en)
+      type: mteb/mtop_intent
+      config: en
+      split: test
+      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
+    metrics:
+    - type: accuracy
+      value: 58.62517099863203
+    - type: f1
+      value: 40.69925681703197
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MasakhaNEWSClassification (eng)
+      type: masakhane/masakhanews
+      config: eng
+      split: test
+      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
+    metrics:
+    - type: accuracy
+      value: 76.29746835443039
+    - type: f1
+      value: 75.31702672039506
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB MasakhaNEWSClusteringP2P (eng)
+      type: masakhane/masakhanews
+      config: eng
+      split: test
+      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
+    metrics:
+    - type: v_measure
+      value: 43.05495067062023
+    - type: v_measure
+      value: 19.625272848173843
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveIntentClassification (en)
+      type: mteb/amazon_massive_intent
+      config: en
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 64.76126429051781
+    - type: f1
+      value: 62.60284261265268
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveScenarioClassification (en)
+      type: mteb/amazon_massive_scenario
+      config: en
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 70.05043712172159
+    - type: f1
+      value: 69.08340521169049
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB MedrxivClusteringP2P
+      type: mteb/medrxiv-clustering-p2p
+      config: default
+      split: test
+      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
+    metrics:
+    - type: v_measure
+      value: 30.78969229005989
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB MedrxivClusteringS2S
+      type: mteb/medrxiv-clustering-s2s
+      config: default
+      split: test
+      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
+    metrics:
+    - type: v_measure
+      value: 27.954325178520335
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB MindSmallReranking
+      type: mteb/mind_small
+      config: default
+      split: test
+      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
+    metrics:
+    - type: map
+      value: 30.601827413968596
+    - type: mrr
+      value: 31.515372019474196
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB NFCorpus
+      type: mteb/nfcorpus
+      config: default
+      split: test
+      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
+    metrics:
+    - type: map_at_1
+      value: 5.4559999999999995
+    - type: map_at_10
+      value: 12.039
+    - type: map_at_100
+      value: 14.804999999999998
+    - type: map_at_1000
+      value: 16.081
+    - type: map_at_3
+      value: 8.996
+    - type: map_at_5
+      value: 10.357
+    - type: mrr_at_1
+      value: 45.82
+    - type: mrr_at_10
+      value: 53.583999999999996
+    - type: mrr_at_100
+      value: 54.330999999999996
+    - type: mrr_at_1000
+      value: 54.366
+    - type: mrr_at_3
+      value: 52.166999999999994
+    - type: mrr_at_5
+      value: 52.971999999999994
+    - type: ndcg_at_1
+      value: 44.427
+    - type: ndcg_at_10
+      value: 32.536
+    - type: ndcg_at_100
+      value: 29.410999999999998
+    - type: ndcg_at_1000
+      value: 38.012
+    - type: ndcg_at_3
+      value: 38.674
+    - type: ndcg_at_5
+      value: 36.107
+    - type: precision_at_1
+      value: 45.82
+    - type: precision_at_10
+      value: 23.591
+    - type: precision_at_100
+      value: 7.35
+    - type: precision_at_1000
+      value: 1.9769999999999999
+    - type: precision_at_3
+      value: 36.016999999999996
+    - type: precision_at_5
+      value: 30.959999999999997
+    - type: recall_at_1
+      value: 5.4559999999999995
+    - type: recall_at_10
+      value: 15.387
+    - type: recall_at_100
+      value: 28.754999999999995
+    - type: recall_at_1000
+      value: 59.787
+    - type: recall_at_3
+      value: 10.137
+    - type: recall_at_5
+      value: 12.200999999999999
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB NQ
+      type: mteb/nq
+      config: default
+      split: test
+      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
+    metrics:
+    - type: map_at_1
+      value: 32.609
+    - type: map_at_10
+      value: 48.522
+    - type: map_at_100
+      value: 49.468
+    - type: map_at_1000
+      value: 49.497
+    - type: map_at_3
+      value: 44.327
+    - type: map_at_5
+      value: 46.937
+    - type: mrr_at_1
+      value: 36.616
+    - type: mrr_at_10
+      value: 50.943000000000005
+    - type: mrr_at_100
+      value: 51.626000000000005
+    - type: mrr_at_1000
+      value: 51.647
+    - type: mrr_at_3
+      value: 47.532999999999994
+    - type: mrr_at_5
+      value: 49.714000000000006
+    - type: ndcg_at_1
+      value: 36.586999999999996
+    - type: ndcg_at_10
+      value: 56.19499999999999
+    - type: ndcg_at_100
+      value: 60.014
+    - type: ndcg_at_1000
+      value: 60.707
+    - type: ndcg_at_3
+      value: 48.486000000000004
+    - type: ndcg_at_5
+      value: 52.791999999999994
+    - type: precision_at_1
+      value: 36.586999999999996
+    - type: precision_at_10
+      value: 9.139999999999999
+    - type: precision_at_100
+      value: 1.129
+    - type: precision_at_1000
+      value: 0.11900000000000001
+    - type: precision_at_3
+      value: 22.171
+    - type: precision_at_5
+      value: 15.787999999999998
+    - type: recall_at_1
+      value: 32.609
+    - type: recall_at_10
+      value: 77.011
+    - type: recall_at_100
+      value: 93.202
+    - type: recall_at_1000
+      value: 98.344
+    - type: recall_at_3
+      value: 57.286
+    - type: recall_at_5
+      value: 67.181
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB NewsClassification
+      type: ag_news
+      config: default
+      split: test
+      revision: eb185aade064a813bc0b7f42de02595523103ca4
+    metrics:
+    - type: accuracy
+      value: 77.4421052631579
+    - type: f1
+      value: 77.23976860913628
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB OpusparcusPC (en)
+      type: GEM/opusparcus
+      config: en
+      split: test
+      revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.89816700610999
+    - type: cos_sim_ap
+      value: 100
+    - type: cos_sim_f1
+      value: 99.9490575649516
+    - type: cos_sim_precision
+      value: 100
+    - type: cos_sim_recall
+      value: 99.89816700610999
+    - type: dot_accuracy
+      value: 99.89816700610999
+    - type: dot_ap
+      value: 100
+    - type: dot_f1
+      value: 99.9490575649516
+    - type: dot_precision
+      value: 100
+    - type: dot_recall
+      value: 99.89816700610999
+    - type: euclidean_accuracy
+      value: 99.89816700610999
+    - type: euclidean_ap
+      value: 100
+    - type: euclidean_f1
+      value: 99.9490575649516
+    - type: euclidean_precision
+      value: 100
+    - type: euclidean_recall
+      value: 99.89816700610999
+    - type: manhattan_accuracy
+      value: 99.89816700610999
+    - type: manhattan_ap
+      value: 100
+    - type: manhattan_f1
+      value: 99.9490575649516
+    - type: manhattan_precision
+      value: 100
+    - type: manhattan_recall
+      value: 99.89816700610999
+    - type: max_accuracy
+      value: 99.89816700610999
+    - type: max_ap
+      value: 100
+    - type: max_f1
+      value: 99.9490575649516
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB PawsX (en)
+      type: paws-x
+      config: en
+      split: test
+      revision: 8a04d940a42cd40658986fdd8e3da561533a3646
+    metrics:
+    - type: cos_sim_accuracy
+      value: 61.25000000000001
+    - type: cos_sim_ap
+      value: 59.23166242799505
+    - type: cos_sim_f1
+      value: 62.53016201309893
+    - type: cos_sim_precision
+      value: 45.486459378134406
+    - type: cos_sim_recall
+      value: 100
+    - type: dot_accuracy
+      value: 61.25000000000001
+    - type: dot_ap
+      value: 59.23109306756652
+    - type: dot_f1
+      value: 62.53016201309893
+    - type: dot_precision
+      value: 45.486459378134406
+    - type: dot_recall
+      value: 100
+    - type: euclidean_accuracy
+      value: 61.25000000000001
+    - type: euclidean_ap
+      value: 59.23166242799505
+    - type: euclidean_f1
+      value: 62.53016201309893
+    - type: euclidean_precision
+      value: 45.486459378134406
+    - type: euclidean_recall
+      value: 100
+    - type: manhattan_accuracy
+      value: 61.25000000000001
+    - type: manhattan_ap
+      value: 59.23015114712089
+    - type: manhattan_f1
+      value: 62.50861474844934
+    - type: manhattan_precision
+      value: 45.46365914786967
+    - type: manhattan_recall
+      value: 100
+    - type: max_accuracy
+      value: 61.25000000000001
+    - type: max_ap
+      value: 59.23166242799505
+    - type: max_f1
+      value: 62.53016201309893
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB QuoraRetrieval
+      type: mteb/quora
+      config: default
+      split: test
+      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
+    metrics:
+    - type: map_at_1
+      value: 69.919
+    - type: map_at_10
+      value: 83.636
+    - type: map_at_100
+      value: 84.27
+    - type: map_at_1000
+      value: 84.289
+    - type: map_at_3
+      value: 80.744
+    - type: map_at_5
+      value: 82.509
+    - type: mrr_at_1
+      value: 80.52
+    - type: mrr_at_10
+      value: 86.751
+    - type: mrr_at_100
+      value: 86.875
+    - type: mrr_at_1000
+      value: 86.876
+    - type: mrr_at_3
+      value: 85.798
+    - type: mrr_at_5
+      value: 86.414
+    - type: ndcg_at_1
+      value: 80.53
+    - type: ndcg_at_10
+      value: 87.465
+    - type: ndcg_at_100
+      value: 88.762
+    - type: ndcg_at_1000
+      value: 88.90599999999999
+    - type: ndcg_at_3
+      value: 84.634
+    - type: ndcg_at_5
+      value: 86.09400000000001
+    - type: precision_at_1
+      value: 80.53
+    - type: precision_at_10
+      value: 13.263
+    - type: precision_at_100
+      value: 1.517
+    - type: precision_at_1000
+      value: 0.156
+    - type: precision_at_3
+      value: 36.973
+    - type: precision_at_5
+      value: 24.25
+    - type: recall_at_1
+      value: 69.919
+    - type: recall_at_10
+      value: 94.742
+    - type: recall_at_100
+      value: 99.221
+    - type: recall_at_1000
+      value: 99.917
+    - type: recall_at_3
+      value: 86.506
+    - type: recall_at_5
+      value: 90.736
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB RedditClustering
+      type: mteb/reddit-clustering
+      config: default
+      split: test
+      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
+    metrics:
+    - type: v_measure
+      value: 50.47309147963901
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB RedditClusteringP2P
+      type: mteb/reddit-clustering-p2p
+      config: default
+      split: test
+      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
+    metrics:
+    - type: v_measure
+      value: 60.53779561923047
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB SCIDOCS
+      type: mteb/scidocs
+      config: default
+      split: test
+      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
+    metrics:
+    - type: map_at_1
+      value: 4.843
+    - type: map_at_10
+      value: 11.664
+    - type: map_at_100
+      value: 13.499
+    - type: map_at_1000
+      value: 13.771
+    - type: map_at_3
+      value: 8.602
+    - type: map_at_5
+      value: 10.164
+    - type: mrr_at_1
+      value: 23.9
+    - type: mrr_at_10
+      value: 34.018
+    - type: mrr_at_100
+      value: 35.099000000000004
+    - type: mrr_at_1000
+      value: 35.162
+    - type: mrr_at_3
+      value: 31.233
+    - type: mrr_at_5
+      value: 32.793
+    - type: ndcg_at_1
+      value: 23.9
+    - type: ndcg_at_10
+      value: 19.42
+    - type: ndcg_at_100
+      value: 26.715
+    - type: ndcg_at_1000
+      value: 31.776
+    - type: ndcg_at_3
+      value: 19.165
+    - type: ndcg_at_5
+      value: 16.46
+    - type: precision_at_1
+      value: 23.9
+    - type: precision_at_10
+      value: 9.82
+    - type: precision_at_100
+      value: 2.0340000000000003
+    - type: precision_at_1000
+      value: 0.325
+    - type: precision_at_3
+      value: 17.767
+    - type: precision_at_5
+      value: 14.24
+    - type: recall_at_1
+      value: 4.843
+    - type: recall_at_10
+      value: 19.895
+    - type: recall_at_100
+      value: 41.302
+    - type: recall_at_1000
+      value: 66.077
+    - type: recall_at_3
+      value: 10.803
+    - type: recall_at_5
+      value: 14.418000000000001
+  - task:
+      type: STS
+    dataset:
+      name: MTEB SICK-R
+      type: mteb/sickr-sts
+      config: default
+      split: test
+      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
+    metrics:
+    - type: cos_sim_pearson
+      value: 76.94120735638143
+    - type: cos_sim_spearman
+      value: 69.66114097154585
+    - type: euclidean_pearson
+      value: 73.11242035696426
+    - type: euclidean_spearman
+      value: 69.66114271982464
+    - type: manhattan_pearson
+      value: 73.07993034858605
+    - type: manhattan_spearman
+      value: 69.6457893357314
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS12
+      type: mteb/sts12-sts
+      config: default
+      split: test
+      revision: a0d554a64d88156834ff5ae9920b964011b16384
+    metrics:
+    - type: cos_sim_pearson
+      value: 74.72893353272778
+    - type: cos_sim_spearman
+      value: 68.78540928870311
+    - type: euclidean_pearson
+      value: 71.13907970605574
+    - type: euclidean_spearman
+      value: 68.78540928870311
+    - type: manhattan_pearson
+      value: 71.02709590547859
+    - type: manhattan_spearman
+      value: 68.71685896660532
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS13
+      type: mteb/sts13-sts
+      config: default
+      split: test
+      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
+    metrics:
+    - type: cos_sim_pearson
+      value: 79.30142652684971
+    - type: cos_sim_spearman
+      value: 79.61879435615303
+    - type: euclidean_pearson
+      value: 79.08730432883864
+    - type: euclidean_spearman
+      value: 79.61879435615303
+    - type: manhattan_pearson
+      value: 78.99621073156322
+    - type: manhattan_spearman
+      value: 79.53806342308278
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS14
+      type: mteb/sts14-sts
+      config: default
+      split: test
+      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
+    metrics:
+    - type: cos_sim_pearson
+      value: 78.99585233036139
+    - type: cos_sim_spearman
+      value: 75.57574519760183
+    - type: euclidean_pearson
+      value: 77.33835658613162
+    - type: euclidean_spearman
+      value: 75.57573873503655
+    - type: manhattan_pearson
+      value: 77.12175044789362
+    - type: manhattan_spearman
+      value: 75.41293517634836
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS15
+      type: mteb/sts15-sts
+      config: default
+      split: test
+      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
+    metrics:
+    - type: cos_sim_pearson
+      value: 83.9694268253376
+    - type: cos_sim_spearman
+      value: 84.64256921939338
+    - type: euclidean_pearson
+      value: 83.92322958711
+    - type: euclidean_spearman
+      value: 84.64257976421872
+    - type: manhattan_pearson
+      value: 83.93503107204337
+    - type: manhattan_spearman
+      value: 84.63611608236032
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS16
+      type: mteb/sts16-sts
+      config: default
+      split: test
+      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.09041419790253
+    - type: cos_sim_spearman
+      value: 82.39869157752557
+    - type: euclidean_pearson
+      value: 82.04595698258301
+    - type: euclidean_spearman
+      value: 82.39869157752557
+    - type: manhattan_pearson
+      value: 81.97581168053004
+    - type: manhattan_spearman
+      value: 82.34255320578193
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS17 (en-en)
+      type: mteb/sts17-crosslingual-sts
+      config: en-en
+      split: test
+      revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d
+    metrics:
+    - type: cos_sim_pearson
+      value: 86.35210432821825
+    - type: cos_sim_spearman
+      value: 86.73200885328937
+    - type: euclidean_pearson
+      value: 86.8527089168747
+    - type: euclidean_spearman
+      value: 86.73200885328937
+    - type: manhattan_pearson
+      value: 86.95671235295457
+    - type: manhattan_spearman
+      value: 86.77713700838545
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS22 (en)
+      type: mteb/sts22-crosslingual-sts
+      config: en
+      split: test
+      revision: eea2b4fe26a775864c896887d910b76a8098ad3f
+    metrics:
+    - type: cos_sim_pearson
+      value: 68.91106612960657
+    - type: cos_sim_spearman
+      value: 69.48524490302286
+    - type: euclidean_pearson
+      value: 70.51347841618035
+    - type: euclidean_spearman
+      value: 69.48524490302286
+    - type: manhattan_pearson
+      value: 70.31770181334245
+    - type: manhattan_spearman
+      value: 69.12494700138238
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STSBenchmark
+      type: mteb/stsbenchmark-sts
+      config: default
+      split: test
+      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.54104342761988
+    - type: cos_sim_spearman
+      value: 81.18789220331483
+    - type: euclidean_pearson
+      value: 81.5895544590969
+    - type: euclidean_spearman
+      value: 81.18789220331483
+    - type: manhattan_pearson
+      value: 81.4738562449809
+    - type: manhattan_spearman
+      value: 81.06565101416024
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STSBenchmarkMultilingualSTS (en)
+      type: PhilipMay/stsb_multi_mt
+      config: en
+      split: test
+      revision: 93d57ef91790589e3ce9c365164337a8a78b7632
+    metrics:
+    - type: cos_sim_pearson
+      value: 81.54104346197056
+    - type: cos_sim_spearman
+      value: 81.18789220331483
+    - type: euclidean_pearson
+      value: 81.58955451690102
+    - type: euclidean_spearman
+      value: 81.18789220331483
+    - type: manhattan_pearson
+      value: 81.47385630064072
+    - type: manhattan_spearman
+      value: 81.06565101416024
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB SciDocsRR
+      type: mteb/scidocs-reranking
+      config: default
+      split: test
+      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
+    metrics:
+    - type: map
+      value: 79.34107964300796
+    - type: mrr
+      value: 94.01917889662987
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB SciFact
+      type: mteb/scifact
+      config: default
+      split: test
+      revision: 0228b52cf27578f30900b9e5271d331663a030d7
+    metrics:
+    - type: map_at_1
+      value: 55.928
+    - type: map_at_10
+      value: 65.443
+    - type: map_at_100
+      value: 66.067
+    - type: map_at_1000
+      value: 66.091
+    - type: map_at_3
+      value: 62.629999999999995
+    - type: map_at_5
+      value: 64.35
+    - type: mrr_at_1
+      value: 59
+    - type: mrr_at_10
+      value: 66.845
+    - type: mrr_at_100
+      value: 67.31899999999999
+    - type: mrr_at_1000
+      value: 67.342
+    - type: mrr_at_3
+      value: 64.61099999999999
+    - type: mrr_at_5
+      value: 66.044
+    - type: ndcg_at_1
+      value: 59
+    - type: ndcg_at_10
+      value: 69.921
+    - type: ndcg_at_100
+      value: 72.365
+    - type: ndcg_at_1000
+      value: 73.055
+    - type: ndcg_at_3
+      value: 65.086
+    - type: ndcg_at_5
+      value: 67.62700000000001
+    - type: precision_at_1
+      value: 59
+    - type: precision_at_10
+      value: 9.3
+    - type: precision_at_100
+      value: 1.057
+    - type: precision_at_1000
+      value: 0.11100000000000002
+    - type: precision_at_3
+      value: 25.333
+    - type: precision_at_5
+      value: 16.866999999999997
+    - type: recall_at_1
+      value: 55.928
+    - type: recall_at_10
+      value: 82.289
+    - type: recall_at_100
+      value: 92.833
+    - type: recall_at_1000
+      value: 98.333
+    - type: recall_at_3
+      value: 69.172
+    - type: recall_at_5
+      value: 75.628
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB SprintDuplicateQuestions
+      type: mteb/sprintduplicatequestions-pairclassification
+      config: default
+      split: test
+      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
+    metrics:
+    - type: cos_sim_accuracy
+      value: 99.81881188118813
+    - type: cos_sim_ap
+      value: 95.2776439040401
+    - type: cos_sim_f1
+      value: 90.74355083459787
+    - type: cos_sim_precision
+      value: 91.81166837256909
+    - type: cos_sim_recall
+      value: 89.7
+    - type: dot_accuracy
+      value: 99.81881188118813
+    - type: dot_ap
+      value: 95.27764092100406
+    - type: dot_f1
+      value: 90.74355083459787
+    - type: dot_precision
+      value: 91.81166837256909
+    - type: dot_recall
+      value: 89.7
+    - type: euclidean_accuracy
+      value: 99.81881188118813
+    - type: euclidean_ap
+      value: 95.27764091101388
+    - type: euclidean_f1
+      value: 90.74355083459787
+    - type: euclidean_precision
+      value: 91.81166837256909
+    - type: euclidean_recall
+      value: 89.7
+    - type: manhattan_accuracy
+      value: 99.82079207920792
+    - type: manhattan_ap
+      value: 95.25081634689418
+    - type: manhattan_f1
+      value: 90.75114971895759
+    - type: manhattan_precision
+      value: 92.78996865203762
+    - type: manhattan_recall
+      value: 88.8
+    - type: max_accuracy
+      value: 99.82079207920792
+    - type: max_ap
+      value: 95.2776439040401
+    - type: max_f1
+      value: 90.75114971895759
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB StackExchangeClustering
+      type: mteb/stackexchange-clustering
+      config: default
+      split: test
+      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
+    metrics:
+    - type: v_measure
+      value: 60.69855369728728
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB StackExchangeClusteringP2P
+      type: mteb/stackexchange-clustering-p2p
+      config: default
+      split: test
+      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
+    metrics:
+    - type: v_measure
+      value: 33.98191834367251
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB StackOverflowDupQuestions
+      type: mteb/stackoverflowdupquestions-reranking
+      config: default
+      split: test
+      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
+    metrics:
+    - type: map
+      value: 50.156163330429614
+    - type: mrr
+      value: 50.90145148968678
+  - task:
+      type: Summarization
+    dataset:
+      name: MTEB SummEval
+      type: mteb/summeval
+      config: default
+      split: test
+      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
+    metrics:
+    - type: cos_sim_pearson
+      value: 31.16938079808134
+    - type: cos_sim_spearman
+      value: 31.74655874538245
+    - type: dot_pearson
+      value: 31.169380299671705
+    - type: dot_spearman
+      value: 31.74655874538245
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB TRECCOVID
+      type: mteb/trec-covid
+      config: default
+      split: test
+      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
+    metrics:
+    - type: map_at_1
+      value: 0.252
+    - type: map_at_10
+      value: 2.009
+    - type: map_at_100
+      value: 11.611
+    - type: map_at_1000
+      value: 27.811999999999998
+    - type: map_at_3
+      value: 0.685
+    - type: map_at_5
+      value: 1.08
+    - type: mrr_at_1
+      value: 94
+    - type: mrr_at_10
+      value: 97
+    - type: mrr_at_100
+      value: 97
+    - type: mrr_at_1000
+      value: 97
+    - type: mrr_at_3
+      value: 97
+    - type: mrr_at_5
+      value: 97
+    - type: ndcg_at_1
+      value: 88
+    - type: ndcg_at_10
+      value: 81.388
+    - type: ndcg_at_100
+      value: 60.629
+    - type: ndcg_at_1000
+      value: 52.38
+    - type: ndcg_at_3
+      value: 86.827
+    - type: ndcg_at_5
+      value: 84.597
+    - type: precision_at_1
+      value: 94
+    - type: precision_at_10
+      value: 85.8
+    - type: precision_at_100
+      value: 62.419999999999995
+    - type: precision_at_1000
+      value: 23.31
+    - type: precision_at_3
+      value: 90.667
+    - type: precision_at_5
+      value: 88.4
+    - type: recall_at_1
+      value: 0.252
+    - type: recall_at_10
+      value: 2.164
+    - type: recall_at_100
+      value: 14.613999999999999
+    - type: recall_at_1000
+      value: 48.730000000000004
+    - type: recall_at_3
+      value: 0.7020000000000001
+    - type: recall_at_5
+      value: 1.122
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB Touche2020
+      type: mteb/touche2020
+      config: default
+      split: test
+      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
+    metrics:
+    - type: map_at_1
+      value: 3.476
+    - type: map_at_10
+      value: 13.442000000000002
+    - type: map_at_100
+      value: 20.618
+    - type: map_at_1000
+      value: 22.175
+    - type: map_at_3
+      value: 6.968000000000001
+    - type: map_at_5
+      value: 9.214
+    - type: mrr_at_1
+      value: 44.897999999999996
+    - type: mrr_at_10
+      value: 56.77100000000001
+    - type: mrr_at_100
+      value: 57.226
+    - type: mrr_at_1000
+      value: 57.226
+    - type: mrr_at_3
+      value: 52.381
+    - type: mrr_at_5
+      value: 54.523999999999994
+    - type: ndcg_at_1
+      value: 42.857
+    - type: ndcg_at_10
+      value: 32.507999999999996
+    - type: ndcg_at_100
+      value: 43.614000000000004
+    - type: ndcg_at_1000
+      value: 53.82
+    - type: ndcg_at_3
+      value: 36.818
+    - type: ndcg_at_5
+      value: 33.346
+    - type: precision_at_1
+      value: 44.897999999999996
+    - type: precision_at_10
+      value: 28.571
+    - type: precision_at_100
+      value: 8.652999999999999
+    - type: precision_at_1000
+      value: 1.5709999999999997
+    - type: precision_at_3
+      value: 38.095
+    - type: precision_at_5
+      value: 32.245000000000005
+    - type: recall_at_1
+      value: 3.476
+    - type: recall_at_10
+      value: 20.827
+    - type: recall_at_100
+      value: 53.04299999999999
+    - type: recall_at_1000
+      value: 84.221
+    - type: recall_at_3
+      value: 8.200000000000001
+    - type: recall_at_5
+      value: 11.651
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB ToxicConversationsClassification
+      type: mteb/toxic_conversations_50k
+      config: default
+      split: test
+      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
+    metrics:
+    - type: accuracy
+      value: 61.96360000000001
+    - type: ap
+      value: 11.256160324436445
+    - type: f1
+      value: 48.07712827691349
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB TweetSentimentExtractionClassification
+      type: mteb/tweet_sentiment_extraction
+      config: default
+      split: test
+      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
+    metrics:
+    - type: accuracy
+      value: 58.90492359932088
+    - type: f1
+      value: 59.12542417513503
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB TwentyNewsgroupsClustering
+      type: mteb/twentynewsgroups-clustering
+      config: default
+      split: test
+      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
+    metrics:
+    - type: v_measure
+      value: 38.284935353315355
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB TwitterSemEval2015
+      type: mteb/twittersemeval2015-pairclassification
+      config: default
+      split: test
+      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
+    metrics:
+    - type: cos_sim_accuracy
+      value: 83.4714192048638
+    - type: cos_sim_ap
+      value: 65.77588263185375
+    - type: cos_sim_f1
+      value: 62.459508098380326
+    - type: cos_sim_precision
+      value: 57.27172717271727
+    - type: cos_sim_recall
+      value: 68.68073878627968
+    - type: dot_accuracy
+      value: 83.4714192048638
+    - type: dot_ap
+      value: 65.77588818364636
+    - type: dot_f1
+      value: 62.459508098380326
+    - type: dot_precision
+      value: 57.27172717271727
+    - type: dot_recall
+      value: 68.68073878627968
+    - type: euclidean_accuracy
+      value: 83.4714192048638
+    - type: euclidean_ap
+      value: 65.77587693431595
+    - type: euclidean_f1
+      value: 62.459508098380326
+    - type: euclidean_precision
+      value: 57.27172717271727
+    - type: euclidean_recall
+      value: 68.68073878627968
+    - type: manhattan_accuracy
+      value: 83.47737974608094
+    - type: manhattan_ap
+      value: 65.65957745829654
+    - type: manhattan_f1
+      value: 62.22760290556902
+    - type: manhattan_precision
+      value: 57.494407158836694
+    - type: manhattan_recall
+      value: 67.81002638522428
+    - type: max_accuracy
+      value: 83.47737974608094
+    - type: max_ap
+      value: 65.77588818364636
+    - type: max_f1
+      value: 62.459508098380326
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB TwitterURLCorpus
+      type: mteb/twitterurlcorpus-pairclassification
+      config: default
+      split: test
+      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
+    metrics:
+    - type: cos_sim_accuracy
+      value: 88.64244964489463
+    - type: cos_sim_ap
+      value: 85.154122301394
+    - type: cos_sim_f1
+      value: 77.45617911327146
+    - type: cos_sim_precision
+      value: 74.23066064370413
+    - type: cos_sim_recall
+      value: 80.97474591931014
+    - type: dot_accuracy
+      value: 88.64244964489463
+    - type: dot_ap
+      value: 85.15411965587543
+    - type: dot_f1
+      value: 77.45617911327146
+    - type: dot_precision
+      value: 74.23066064370413
+    - type: dot_recall
+      value: 80.97474591931014
+    - type: euclidean_accuracy
+      value: 88.64244964489463
+    - type: euclidean_ap
+      value: 85.15414684113986
+    - type: euclidean_f1
+      value: 77.45617911327146
+    - type: euclidean_precision
+      value: 74.23066064370413
+    - type: euclidean_recall
+      value: 80.97474591931014
+    - type: manhattan_accuracy
+      value: 88.57841425078588
+    - type: manhattan_ap
+      value: 85.12472268567576
+    - type: manhattan_f1
+      value: 77.39497339937627
+    - type: manhattan_precision
+      value: 73.92584285413892
+    - type: manhattan_recall
+      value: 81.20572836464429
+    - type: max_accuracy
+      value: 88.64244964489463
+    - type: max_ap
+      value: 85.15414684113986
+    - type: max_f1
+      value: 77.45617911327146
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB WikiCitiesClustering
+      type: jinaai/cities_wiki_clustering
+      config: default
+      split: test
+      revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
+    metrics:
+    - type: v_measure
+      value: 79.58576208710117
+---
+
+# yishan-wang/snowflake-arctic-embed-s-Q8_0-GGUF
+This model was converted to GGUF format from [`Snowflake/snowflake-arctic-embed-s`](https://huggingface.co/Snowflake/snowflake-arctic-embed-s) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
+Refer to the [original model card](https://huggingface.co/Snowflake/snowflake-arctic-embed-s) for more details on the model.
+
+## Use with llama.cpp
+Install llama.cpp through brew (works on Mac and Linux)
+
+```bash
+brew install llama.cpp
+
+```
+Invoke the llama.cpp server or the CLI.
+
+### CLI:
+```bash
+llama-cli --hf-repo yishan-wang/snowflake-arctic-embed-s-Q8_0-GGUF --hf-file snowflake-arctic-embed-s-q8_0.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo yishan-wang/snowflake-arctic-embed-s-Q8_0-GGUF --hf-file snowflake-arctic-embed-s-q8_0.gguf -c 2048
+```
+
+Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
+
+Step 1: Clone llama.cpp from GitHub.
+```
+git clone https://github.com/ggerganov/llama.cpp
+```
+
+Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
+```
+cd llama.cpp && LLAMA_CURL=1 make
+```
+
+Step 3: Run inference through the main binary.
+```
+./llama-cli --hf-repo yishan-wang/snowflake-arctic-embed-s-Q8_0-GGUF --hf-file snowflake-arctic-embed-s-q8_0.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo yishan-wang/snowflake-arctic-embed-s-Q8_0-GGUF --hf-file snowflake-arctic-embed-s-q8_0.gguf -c 2048
+```