sentence-transformers gguf feature-extraction sentence-similarity mteb arctic snowflake-arctic-embed transformers.js llama-cpp gguf-my-repo base_model:Snowflake/snowflake-arctic-embed-m-long base_model:quantized:Snowflake/snowflake-arctic-embed-m-long license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: Snowflake/snowflake-arctic-embed-m-long
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-arctic-m-long
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 78.4776119402985
    - type: ap
      value: 42.34374238166049
    - type: f1
      value: 72.51164234732224
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 78.7416
    - type: ap
      value: 73.12074819362377
    - type: f1
      value: 78.64057339708795
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 39.926
    - type: f1
      value: 39.35531993117573
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 34.851
    - type: map_at_10
      value: 51.473
    - type: map_at_100
      value: 52.103
    - type: map_at_1000
      value: 52.105000000000004
    - type: map_at_3
      value: 46.776
    - type: map_at_5
      value: 49.617
    - type: mrr_at_1
      value: 35.491
    - type: mrr_at_10
      value: 51.73799999999999
    - type: mrr_at_100
      value: 52.37500000000001
    - type: mrr_at_1000
      value: 52.378
    - type: mrr_at_3
      value: 46.965
    - type: mrr_at_5
      value: 49.878
    - type: ndcg_at_1
      value: 34.851
    - type: ndcg_at_10
      value: 60.364
    - type: ndcg_at_100
      value: 62.888999999999996
    - type: ndcg_at_1000
      value: 62.946000000000005
    - type: ndcg_at_3
      value: 50.807
    - type: ndcg_at_5
      value: 55.901
    - type: precision_at_1
      value: 34.851
    - type: precision_at_10
      value: 8.855
    - type: precision_at_100
      value: 0.992
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 20.839
    - type: precision_at_5
      value: 14.963999999999999
    - type: recall_at_1
      value: 34.851
    - type: recall_at_10
      value: 88.549
    - type: recall_at_100
      value: 99.21799999999999
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_3
      value: 62.517999999999994
    - type: recall_at_5
      value: 74.822
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 45.5554998405317
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 35.614248811397005
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 61.355489424753884
    - type: mrr
      value: 75.49443784900849
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 89.17311056578292
    - type: cos_sim_spearman
      value: 88.24237210809322
    - type: euclidean_pearson
      value: 87.3188065853646
    - type: euclidean_spearman
      value: 88.24237210809322
    - type: manhattan_pearson
      value: 86.89499710049658
    - type: manhattan_spearman
      value: 87.85441146091777
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 80.26298701298703
    - type: f1
      value: 79.68356764080303
  - task:
      type: Clustering
    dataset:
      name: MTEB BigPatentClustering
      type: jinaai/big-patent-clustering
      config: default
      split: test
      revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
    metrics:
    - type: v_measure
      value: 20.923883720813706
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 36.16058801465044
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 30.1402356118627
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: mteb/cqadupstack-android
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 35.612
    - type: map_at_10
      value: 47.117
    - type: map_at_100
      value: 48.711
    - type: map_at_1000
      value: 48.826
    - type: map_at_3
      value: 43.858999999999995
    - type: map_at_5
      value: 45.612
    - type: mrr_at_1
      value: 42.918
    - type: mrr_at_10
      value: 52.806
    - type: mrr_at_100
      value: 53.564
    - type: mrr_at_1000
      value: 53.596999999999994
    - type: mrr_at_3
      value: 50.453
    - type: mrr_at_5
      value: 51.841
    - type: ndcg_at_1
      value: 42.918
    - type: ndcg_at_10
      value: 53.291999999999994
    - type: ndcg_at_100
      value: 58.711999999999996
    - type: ndcg_at_1000
      value: 60.317
    - type: ndcg_at_3
      value: 48.855
    - type: ndcg_at_5
      value: 50.778
    - type: precision_at_1
      value: 42.918
    - type: precision_at_10
      value: 9.927999999999999
    - type: precision_at_100
      value: 1.592
    - type: precision_at_1000
      value: 0.201
    - type: precision_at_3
      value: 23.366999999999997
    - type: precision_at_5
      value: 16.366
    - type: recall_at_1
      value: 35.612
    - type: recall_at_10
      value: 64.671
    - type: recall_at_100
      value: 86.97
    - type: recall_at_1000
      value: 96.99600000000001
    - type: recall_at_3
      value: 51.37199999999999
    - type: recall_at_5
      value: 57.094
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: mteb/cqadupstack-english
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 33.742
    - type: map_at_10
      value: 44.49
    - type: map_at_100
      value: 45.781
    - type: map_at_1000
      value: 45.902
    - type: map_at_3
      value: 41.453
    - type: map_at_5
      value: 43.251
    - type: mrr_at_1
      value: 42.357
    - type: mrr_at_10
      value: 50.463
    - type: mrr_at_100
      value: 51.17
    - type: mrr_at_1000
      value: 51.205999999999996
    - type: mrr_at_3
      value: 48.397
    - type: mrr_at_5
      value: 49.649
    - type: ndcg_at_1
      value: 42.357
    - type: ndcg_at_10
      value: 50.175000000000004
    - type: ndcg_at_100
      value: 54.491
    - type: ndcg_at_1000
      value: 56.282
    - type: ndcg_at_3
      value: 46.159
    - type: ndcg_at_5
      value: 48.226
    - type: precision_at_1
      value: 42.357
    - type: precision_at_10
      value: 9.382
    - type: precision_at_100
      value: 1.473
    - type: precision_at_1000
      value: 0.191
    - type: precision_at_3
      value: 22.187
    - type: precision_at_5
      value: 15.758
    - type: recall_at_1
      value: 33.742
    - type: recall_at_10
      value: 59.760999999999996
    - type: recall_at_100
      value: 77.89500000000001
    - type: recall_at_1000
      value: 89.005
    - type: recall_at_3
      value: 47.872
    - type: recall_at_5
      value: 53.559
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: mteb/cqadupstack-gaming
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 43.883
    - type: map_at_10
      value: 56.464999999999996
    - type: map_at_100
      value: 57.394
    - type: map_at_1000
      value: 57.443999999999996
    - type: map_at_3
      value: 53.169
    - type: map_at_5
      value: 54.984
    - type: mrr_at_1
      value: 50.470000000000006
    - type: mrr_at_10
      value: 59.997
    - type: mrr_at_100
      value: 60.586
    - type: mrr_at_1000
      value: 60.61
    - type: mrr_at_3
      value: 57.837
    - type: mrr_at_5
      value: 59.019
    - type: ndcg_at_1
      value: 50.470000000000006
    - type: ndcg_at_10
      value: 62.134
    - type: ndcg_at_100
      value: 65.69500000000001
    - type: ndcg_at_1000
      value: 66.674
    - type: ndcg_at_3
      value: 56.916999999999994
    - type: ndcg_at_5
      value: 59.312
    - type: precision_at_1
      value: 50.470000000000006
    - type: precision_at_10
      value: 9.812
    - type: precision_at_100
      value: 1.25
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_3
      value: 25.119999999999997
    - type: precision_at_5
      value: 17.016000000000002
    - type: recall_at_1
      value: 43.883
    - type: recall_at_10
      value: 75.417
    - type: recall_at_100
      value: 90.545
    - type: recall_at_1000
      value: 97.44500000000001
    - type: recall_at_3
      value: 61.306000000000004
    - type: recall_at_5
      value: 67.244
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: mteb/cqadupstack-gis
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 29.813000000000002
    - type: map_at_10
      value: 38.627
    - type: map_at_100
      value: 39.735
    - type: map_at_1000
      value: 39.806000000000004
    - type: map_at_3
      value: 36.283
    - type: map_at_5
      value: 37.491
    - type: mrr_at_1
      value: 32.316
    - type: mrr_at_10
      value: 40.752
    - type: mrr_at_100
      value: 41.699000000000005
    - type: mrr_at_1000
      value: 41.749
    - type: mrr_at_3
      value: 38.531
    - type: mrr_at_5
      value: 39.706
    - type: ndcg_at_1
      value: 32.316
    - type: ndcg_at_10
      value: 43.524
    - type: ndcg_at_100
      value: 48.648
    - type: ndcg_at_1000
      value: 50.405
    - type: ndcg_at_3
      value: 38.928000000000004
    - type: ndcg_at_5
      value: 40.967
    - type: precision_at_1
      value: 32.316
    - type: precision_at_10
      value: 6.451999999999999
    - type: precision_at_100
      value: 0.9490000000000001
    - type: precision_at_1000
      value: 0.11299999999999999
    - type: precision_at_3
      value: 16.384
    - type: precision_at_5
      value: 11.006
    - type: recall_at_1
      value: 29.813000000000002
    - type: recall_at_10
      value: 56.562999999999995
    - type: recall_at_100
      value: 79.452
    - type: recall_at_1000
      value: 92.715
    - type: recall_at_3
      value: 43.985
    - type: recall_at_5
      value: 49.001
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: mteb/cqadupstack-mathematica
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 19.961000000000002
    - type: map_at_10
      value: 28.026
    - type: map_at_100
      value: 29.212
    - type: map_at_1000
      value: 29.332
    - type: map_at_3
      value: 25.296999999999997
    - type: map_at_5
      value: 26.832
    - type: mrr_at_1
      value: 24.627
    - type: mrr_at_10
      value: 33.045
    - type: mrr_at_100
      value: 33.944
    - type: mrr_at_1000
      value: 34.013
    - type: mrr_at_3
      value: 30.307000000000002
    - type: mrr_at_5
      value: 31.874000000000002
    - type: ndcg_at_1
      value: 24.627
    - type: ndcg_at_10
      value: 33.414
    - type: ndcg_at_100
      value: 39.061
    - type: ndcg_at_1000
      value: 41.795
    - type: ndcg_at_3
      value: 28.377000000000002
    - type: ndcg_at_5
      value: 30.781999999999996
    - type: precision_at_1
      value: 24.627
    - type: precision_at_10
      value: 6.02
    - type: precision_at_100
      value: 1.035
    - type: precision_at_1000
      value: 0.13899999999999998
    - type: precision_at_3
      value: 13.516
    - type: precision_at_5
      value: 9.851
    - type: recall_at_1
      value: 19.961000000000002
    - type: recall_at_10
      value: 45.174
    - type: recall_at_100
      value: 69.69
    - type: recall_at_1000
      value: 89.24600000000001
    - type: recall_at_3
      value: 31.062
    - type: recall_at_5
      value: 37.193
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: mteb/cqadupstack-physics
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 32.080999999999996
    - type: map_at_10
      value: 42.177
    - type: map_at_100
      value: 43.431999999999995
    - type: map_at_1000
      value: 43.533
    - type: map_at_3
      value: 38.721
    - type: map_at_5
      value: 40.669
    - type: mrr_at_1
      value: 38.787
    - type: mrr_at_10
      value: 47.762
    - type: mrr_at_100
      value: 48.541000000000004
    - type: mrr_at_1000
      value: 48.581
    - type: mrr_at_3
      value: 45.123999999999995
    - type: mrr_at_5
      value: 46.639
    - type: ndcg_at_1
      value: 38.787
    - type: ndcg_at_10
      value: 48.094
    - type: ndcg_at_100
      value: 53.291
    - type: ndcg_at_1000
      value: 55.21
    - type: ndcg_at_3
      value: 42.721
    - type: ndcg_at_5
      value: 45.301
    - type: precision_at_1
      value: 38.787
    - type: precision_at_10
      value: 8.576
    - type: precision_at_100
      value: 1.306
    - type: precision_at_1000
      value: 0.164
    - type: precision_at_3
      value: 19.698
    - type: precision_at_5
      value: 14.013
    - type: recall_at_1
      value: 32.080999999999996
    - type: recall_at_10
      value: 59.948
    - type: recall_at_100
      value: 81.811
    - type: recall_at_1000
      value: 94.544
    - type: recall_at_3
      value: 44.903999999999996
    - type: recall_at_5
      value: 51.763999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: mteb/cqadupstack-programmers
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 28.869
    - type: map_at_10
      value: 38.954
    - type: map_at_100
      value: 40.233000000000004
    - type: map_at_1000
      value: 40.332
    - type: map_at_3
      value: 35.585
    - type: map_at_5
      value: 37.476
    - type: mrr_at_1
      value: 35.959
    - type: mrr_at_10
      value: 44.800000000000004
    - type: mrr_at_100
      value: 45.609
    - type: mrr_at_1000
      value: 45.655
    - type: mrr_at_3
      value: 42.333
    - type: mrr_at_5
      value: 43.68
    - type: ndcg_at_1
      value: 35.959
    - type: ndcg_at_10
      value: 44.957
    - type: ndcg_at_100
      value: 50.275000000000006
    - type: ndcg_at_1000
      value: 52.29899999999999
    - type: ndcg_at_3
      value: 39.797
    - type: ndcg_at_5
      value: 42.128
    - type: precision_at_1
      value: 35.959
    - type: precision_at_10
      value: 8.185
    - type: precision_at_100
      value: 1.261
    - type: precision_at_1000
      value: 0.159
    - type: precision_at_3
      value: 18.988
    - type: precision_at_5
      value: 13.516
    - type: recall_at_1
      value: 28.869
    - type: recall_at_10
      value: 57.154
    - type: recall_at_100
      value: 79.764
    - type: recall_at_1000
      value: 93.515
    - type: recall_at_3
      value: 42.364000000000004
    - type: recall_at_5
      value: 48.756
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 29.31008333333333
    - type: map_at_10
      value: 38.81849999999999
    - type: map_at_100
      value: 40.05058333333334
    - type: map_at_1000
      value: 40.16116666666667
    - type: map_at_3
      value: 35.91441666666667
    - type: map_at_5
      value: 37.526583333333335
    - type: mrr_at_1
      value: 34.60066666666667
    - type: mrr_at_10
      value: 43.08858333333333
    - type: mrr_at_100
      value: 43.927749999999996
    - type: mrr_at_1000
      value: 43.97866666666667
    - type: mrr_at_3
      value: 40.72775
    - type: mrr_at_5
      value: 42.067249999999994
    - type: ndcg_at_1
      value: 34.60066666666667
    - type: ndcg_at_10
      value: 44.20841666666667
    - type: ndcg_at_100
      value: 49.32866666666667
    - type: ndcg_at_1000
      value: 51.373999999999995
    - type: ndcg_at_3
      value: 39.452083333333334
    - type: ndcg_at_5
      value: 41.67
    - type: precision_at_1
      value: 34.60066666666667
    - type: precision_at_10
      value: 7.616583333333334
    - type: precision_at_100
      value: 1.20175
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 17.992
    - type: precision_at_5
      value: 12.658416666666666
    - type: recall_at_1
      value: 29.31008333333333
    - type: recall_at_10
      value: 55.81900000000001
    - type: recall_at_100
      value: 78.06308333333334
    - type: recall_at_1000
      value: 92.10641666666668
    - type: recall_at_3
      value: 42.50166666666667
    - type: recall_at_5
      value: 48.26108333333333
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: mteb/cqadupstack-stats
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 26.773000000000003
    - type: map_at_10
      value: 34.13
    - type: map_at_100
      value: 35.113
    - type: map_at_1000
      value: 35.211
    - type: map_at_3
      value: 31.958
    - type: map_at_5
      value: 33.080999999999996
    - type: mrr_at_1
      value: 30.061
    - type: mrr_at_10
      value: 37.061
    - type: mrr_at_100
      value: 37.865
    - type: mrr_at_1000
      value: 37.939
    - type: mrr_at_3
      value: 34.995
    - type: mrr_at_5
      value: 36.092
    - type: ndcg_at_1
      value: 30.061
    - type: ndcg_at_10
      value: 38.391999999999996
    - type: ndcg_at_100
      value: 43.13
    - type: ndcg_at_1000
      value: 45.449
    - type: ndcg_at_3
      value: 34.411
    - type: ndcg_at_5
      value: 36.163000000000004
    - type: precision_at_1
      value: 30.061
    - type: precision_at_10
      value: 5.982
    - type: precision_at_100
      value: 0.911
    - type: precision_at_1000
      value: 0.11800000000000001
    - type: precision_at_3
      value: 14.673
    - type: precision_at_5
      value: 10.030999999999999
    - type: recall_at_1
      value: 26.773000000000003
    - type: recall_at_10
      value: 48.445
    - type: recall_at_100
      value: 69.741
    - type: recall_at_1000
      value: 86.59
    - type: recall_at_3
      value: 37.576
    - type: recall_at_5
      value: 41.948
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: mteb/cqadupstack-tex
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 18.556
    - type: map_at_10
      value: 26.340999999999998
    - type: map_at_100
      value: 27.560000000000002
    - type: map_at_1000
      value: 27.685
    - type: map_at_3
      value: 24.136
    - type: map_at_5
      value: 25.34
    - type: mrr_at_1
      value: 22.368
    - type: mrr_at_10
      value: 30.192999999999998
    - type: mrr_at_100
      value: 31.183
    - type: mrr_at_1000
      value: 31.258000000000003
    - type: mrr_at_3
      value: 28.223
    - type: mrr_at_5
      value: 29.294999999999998
    - type: ndcg_at_1
      value: 22.368
    - type: ndcg_at_10
      value: 31.029
    - type: ndcg_at_100
      value: 36.768
    - type: ndcg_at_1000
      value: 39.572
    - type: ndcg_at_3
      value: 27.197
    - type: ndcg_at_5
      value: 28.912
    - type: precision_at_1
      value: 22.368
    - type: precision_at_10
      value: 5.606
    - type: precision_at_100
      value: 0.9979999999999999
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_3
      value: 12.892999999999999
    - type: precision_at_5
      value: 9.16
    - type: recall_at_1
      value: 18.556
    - type: recall_at_10
      value: 41.087
    - type: recall_at_100
      value: 66.92
    - type: recall_at_1000
      value: 86.691
    - type: recall_at_3
      value: 30.415
    - type: recall_at_5
      value: 34.813
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: mteb/cqadupstack-unix
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 29.953999999999997
    - type: map_at_10
      value: 39.633
    - type: map_at_100
      value: 40.923
    - type: map_at_1000
      value: 41.016000000000005
    - type: map_at_3
      value: 36.609
    - type: map_at_5
      value: 38.443
    - type: mrr_at_1
      value: 35.354
    - type: mrr_at_10
      value: 43.718
    - type: mrr_at_100
      value: 44.651999999999994
    - type: mrr_at_1000
      value: 44.696000000000005
    - type: mrr_at_3
      value: 41.154
    - type: mrr_at_5
      value: 42.730000000000004
    - type: ndcg_at_1
      value: 35.354
    - type: ndcg_at_10
      value: 44.933
    - type: ndcg_at_100
      value: 50.577000000000005
    - type: ndcg_at_1000
      value: 52.428
    - type: ndcg_at_3
      value: 39.833
    - type: ndcg_at_5
      value: 42.465
    - type: precision_at_1
      value: 35.354
    - type: precision_at_10
      value: 7.416
    - type: precision_at_100
      value: 1.157
    - type: precision_at_1000
      value: 0.14100000000000001
    - type: precision_at_3
      value: 17.817
    - type: precision_at_5
      value: 12.687000000000001
    - type: recall_at_1
      value: 29.953999999999997
    - type: recall_at_10
      value: 56.932
    - type: recall_at_100
      value: 80.93900000000001
    - type: recall_at_1000
      value: 93.582
    - type: recall_at_3
      value: 43.192
    - type: recall_at_5
      value: 49.757
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: mteb/cqadupstack-webmasters
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 27.85
    - type: map_at_10
      value: 37.68
    - type: map_at_100
      value: 39.295
    - type: map_at_1000
      value: 39.527
    - type: map_at_3
      value: 35.036
    - type: map_at_5
      value: 36.269
    - type: mrr_at_1
      value: 33.004
    - type: mrr_at_10
      value: 42.096000000000004
    - type: mrr_at_100
      value: 43.019
    - type: mrr_at_1000
      value: 43.071
    - type: mrr_at_3
      value: 39.987
    - type: mrr_at_5
      value: 40.995
    - type: ndcg_at_1
      value: 33.004
    - type: ndcg_at_10
      value: 43.461
    - type: ndcg_at_100
      value: 49.138
    - type: ndcg_at_1000
      value: 51.50900000000001
    - type: ndcg_at_3
      value: 39.317
    - type: ndcg_at_5
      value: 40.760999999999996
    - type: precision_at_1
      value: 33.004
    - type: precision_at_10
      value: 8.161999999999999
    - type: precision_at_100
      value: 1.583
    - type: precision_at_1000
      value: 0.245
    - type: precision_at_3
      value: 18.445
    - type: precision_at_5
      value: 12.885
    - type: recall_at_1
      value: 27.85
    - type: recall_at_10
      value: 54.419
    - type: recall_at_100
      value: 79.742
    - type: recall_at_1000
      value: 93.97
    - type: recall_at_3
      value: 42.149
    - type: recall_at_5
      value: 46.165
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: mteb/cqadupstack-wordpress
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 24.627
    - type: map_at_10
      value: 32.182
    - type: map_at_100
      value: 33.217999999999996
    - type: map_at_1000
      value: 33.32
    - type: map_at_3
      value: 28.866999999999997
    - type: map_at_5
      value: 30.871
    - type: mrr_at_1
      value: 26.987
    - type: mrr_at_10
      value: 34.37
    - type: mrr_at_100
      value: 35.301
    - type: mrr_at_1000
      value: 35.369
    - type: mrr_at_3
      value: 31.391999999999996
    - type: mrr_at_5
      value: 33.287
    - type: ndcg_at_1
      value: 26.987
    - type: ndcg_at_10
      value: 37.096000000000004
    - type: ndcg_at_100
      value: 42.158
    - type: ndcg_at_1000
      value: 44.548
    - type: ndcg_at_3
      value: 30.913
    - type: ndcg_at_5
      value: 34.245
    - type: precision_at_1
      value: 26.987
    - type: precision_at_10
      value: 5.878
    - type: precision_at_100
      value: 0.906
    - type: precision_at_1000
      value: 0.123
    - type: precision_at_3
      value: 12.815999999999999
    - type: precision_at_5
      value: 9.612
    - type: recall_at_1
      value: 24.627
    - type: recall_at_10
      value: 50.257
    - type: recall_at_100
      value: 73.288
    - type: recall_at_1000
      value: 90.97800000000001
    - type: recall_at_3
      value: 33.823
    - type: recall_at_5
      value: 41.839
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: mteb/climate-fever
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 17.343
    - type: map_at_10
      value: 28.59
    - type: map_at_100
      value: 30.591
    - type: map_at_1000
      value: 30.759999999999998
    - type: map_at_3
      value: 24.197
    - type: map_at_5
      value: 26.433
    - type: mrr_at_1
      value: 39.609
    - type: mrr_at_10
      value: 51.107
    - type: mrr_at_100
      value: 51.87199999999999
    - type: mrr_at_1000
      value: 51.894
    - type: mrr_at_3
      value: 48.154
    - type: mrr_at_5
      value: 49.939
    - type: ndcg_at_1
      value: 39.609
    - type: ndcg_at_10
      value: 38.329
    - type: ndcg_at_100
      value: 45.573
    - type: ndcg_at_1000
      value: 48.405
    - type: ndcg_at_3
      value: 32.506
    - type: ndcg_at_5
      value: 34.331
    - type: precision_at_1
      value: 39.609
    - type: precision_at_10
      value: 11.668000000000001
    - type: precision_at_100
      value: 1.9539999999999997
    - type: precision_at_1000
      value: 0.249
    - type: precision_at_3
      value: 23.952
    - type: precision_at_5
      value: 17.902
    - type: recall_at_1
      value: 17.343
    - type: recall_at_10
      value: 43.704
    - type: recall_at_100
      value: 68.363
    - type: recall_at_1000
      value: 84.04599999999999
    - type: recall_at_3
      value: 29.028
    - type: recall_at_5
      value: 35.022
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: mteb/dbpedia
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 9.934999999999999
    - type: map_at_10
      value: 22.081
    - type: map_at_100
      value: 32.036
    - type: map_at_1000
      value: 33.803
    - type: map_at_3
      value: 15.687999999999999
    - type: map_at_5
      value: 18.357
    - type: mrr_at_1
      value: 70.75
    - type: mrr_at_10
      value: 78.506
    - type: mrr_at_100
      value: 78.874
    - type: mrr_at_1000
      value: 78.88300000000001
    - type: mrr_at_3
      value: 77.667
    - type: mrr_at_5
      value: 78.342
    - type: ndcg_at_1
      value: 57.25
    - type: ndcg_at_10
      value: 45.286
    - type: ndcg_at_100
      value: 50.791
    - type: ndcg_at_1000
      value: 58.021
    - type: ndcg_at_3
      value: 49.504
    - type: ndcg_at_5
      value: 47.03
    - type: precision_at_1
      value: 70.75
    - type: precision_at_10
      value: 36.425000000000004
    - type: precision_at_100
      value: 11.953
    - type: precision_at_1000
      value: 2.248
    - type: precision_at_3
      value: 53.25
    - type: precision_at_5
      value: 46.150000000000006
    - type: recall_at_1
      value: 9.934999999999999
    - type: recall_at_10
      value: 27.592
    - type: recall_at_100
      value: 58.089
    - type: recall_at_1000
      value: 81.025
    - type: recall_at_3
      value: 17.048
    - type: recall_at_5
      value: 20.834
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 47.25999999999999
    - type: f1
      value: 43.83371155132253
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: mteb/fever
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 73.68900000000001
    - type: map_at_10
      value: 82.878
    - type: map_at_100
      value: 83.084
    - type: map_at_1000
      value: 83.097
    - type: map_at_3
      value: 81.528
    - type: map_at_5
      value: 82.432
    - type: mrr_at_1
      value: 79.49300000000001
    - type: mrr_at_10
      value: 87.24300000000001
    - type: mrr_at_100
      value: 87.3
    - type: mrr_at_1000
      value: 87.301
    - type: mrr_at_3
      value: 86.359
    - type: mrr_at_5
      value: 87.01
    - type: ndcg_at_1
      value: 79.49300000000001
    - type: ndcg_at_10
      value: 86.894
    - type: ndcg_at_100
      value: 87.6
    - type: ndcg_at_1000
      value: 87.79299999999999
    - type: ndcg_at_3
      value: 84.777
    - type: ndcg_at_5
      value: 86.08
    - type: precision_at_1
      value: 79.49300000000001
    - type: precision_at_10
      value: 10.578
    - type: precision_at_100
      value: 1.117
    - type: precision_at_1000
      value: 0.11499999999999999
    - type: precision_at_3
      value: 32.592999999999996
    - type: precision_at_5
      value: 20.423
    - type: recall_at_1
      value: 73.68900000000001
    - type: recall_at_10
      value: 94.833
    - type: recall_at_100
      value: 97.554
    - type: recall_at_1000
      value: 98.672
    - type: recall_at_3
      value: 89.236
    - type: recall_at_5
      value: 92.461
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: mteb/fiqa
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 20.59
    - type: map_at_10
      value: 34.089000000000006
    - type: map_at_100
      value: 35.796
    - type: map_at_1000
      value: 35.988
    - type: map_at_3
      value: 29.877
    - type: map_at_5
      value: 32.202999999999996
    - type: mrr_at_1
      value: 41.049
    - type: mrr_at_10
      value: 50.370000000000005
    - type: mrr_at_100
      value: 51.209
    - type: mrr_at_1000
      value: 51.247
    - type: mrr_at_3
      value: 48.122
    - type: mrr_at_5
      value: 49.326
    - type: ndcg_at_1
      value: 41.049
    - type: ndcg_at_10
      value: 42.163000000000004
    - type: ndcg_at_100
      value: 48.638999999999996
    - type: ndcg_at_1000
      value: 51.775000000000006
    - type: ndcg_at_3
      value: 38.435
    - type: ndcg_at_5
      value: 39.561
    - type: precision_at_1
      value: 41.049
    - type: precision_at_10
      value: 11.481
    - type: precision_at_100
      value: 1.8239999999999998
    - type: precision_at_1000
      value: 0.24
    - type: precision_at_3
      value: 25.257
    - type: precision_at_5
      value: 18.519
    - type: recall_at_1
      value: 20.59
    - type: recall_at_10
      value: 49.547999999999995
    - type: recall_at_100
      value: 73.676
    - type: recall_at_1000
      value: 92.269
    - type: recall_at_3
      value: 35.656
    - type: recall_at_5
      value: 41.455
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: mteb/hotpotqa
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 39.932
    - type: map_at_10
      value: 64.184
    - type: map_at_100
      value: 65.06
    - type: map_at_1000
      value: 65.109
    - type: map_at_3
      value: 60.27
    - type: map_at_5
      value: 62.732
    - type: mrr_at_1
      value: 79.865
    - type: mrr_at_10
      value: 85.99799999999999
    - type: mrr_at_100
      value: 86.13
    - type: mrr_at_1000
      value: 86.13300000000001
    - type: mrr_at_3
      value: 85.136
    - type: mrr_at_5
      value: 85.69200000000001
    - type: ndcg_at_1
      value: 79.865
    - type: ndcg_at_10
      value: 72.756
    - type: ndcg_at_100
      value: 75.638
    - type: ndcg_at_1000
      value: 76.589
    - type: ndcg_at_3
      value: 67.38199999999999
    - type: ndcg_at_5
      value: 70.402
    - type: precision_at_1
      value: 79.865
    - type: precision_at_10
      value: 15.387999999999998
    - type: precision_at_100
      value: 1.7610000000000001
    - type: precision_at_1000
      value: 0.189
    - type: precision_at_3
      value: 43.394
    - type: precision_at_5
      value: 28.424
    - type: recall_at_1
      value: 39.932
    - type: recall_at_10
      value: 76.941
    - type: recall_at_100
      value: 88.062
    - type: recall_at_1000
      value: 94.396
    - type: recall_at_3
      value: 65.091
    - type: recall_at_5
      value: 71.06
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 71.7904
    - type: ap
      value: 65.82899456730257
    - type: f1
      value: 71.56611877410202
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: mteb/msmarco
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 21.931
    - type: map_at_10
      value: 34.849999999999994
    - type: map_at_100
      value: 36.033
    - type: map_at_1000
      value: 36.08
    - type: map_at_3
      value: 30.842000000000002
    - type: map_at_5
      value: 33.229
    - type: mrr_at_1
      value: 22.55
    - type: mrr_at_10
      value: 35.436
    - type: mrr_at_100
      value: 36.563
    - type: mrr_at_1000
      value: 36.604
    - type: mrr_at_3
      value: 31.507
    - type: mrr_at_5
      value: 33.851
    - type: ndcg_at_1
      value: 22.55
    - type: ndcg_at_10
      value: 41.969
    - type: ndcg_at_100
      value: 47.576
    - type: ndcg_at_1000
      value: 48.731
    - type: ndcg_at_3
      value: 33.894000000000005
    - type: ndcg_at_5
      value: 38.133
    - type: precision_at_1
      value: 22.55
    - type: precision_at_10
      value: 6.660000000000001
    - type: precision_at_100
      value: 0.946
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 14.532
    - type: precision_at_5
      value: 10.865
    - type: recall_at_1
      value: 21.931
    - type: recall_at_10
      value: 63.841
    - type: recall_at_100
      value: 89.47699999999999
    - type: recall_at_1000
      value: 98.259
    - type: recall_at_3
      value: 42.063
    - type: recall_at_5
      value: 52.21
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 93.03921568627452
    - type: f1
      value: 92.56400672314416
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 63.515731874145
    - type: f1
      value: 44.922310875523216
  - task:
      type: Classification
    dataset:
      name: MTEB MasakhaNEWSClassification (eng)
      type: masakhane/masakhanews
      config: eng
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: accuracy
      value: 77.57383966244727
    - type: f1
      value: 76.55222378218293
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (eng)
      type: masakhane/masakhanews
      config: eng
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: v_measure
      value: 62.74836240280833
    - type: v_measure
      value: 24.414348715238184
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 66.54673839946201
    - type: f1
      value: 64.61004101532164
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 73.11365164761264
    - type: f1
      value: 72.01684013680978
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 31.123671999617297
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 26.72684341430875
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.910228061734816
    - type: mrr
      value: 30.835255982532477
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 5.6770000000000005
    - type: map_at_10
      value: 13.15
    - type: map_at_100
      value: 16.205
    - type: map_at_1000
      value: 17.580000000000002
    - type: map_at_3
      value: 9.651
    - type: map_at_5
      value: 11.142000000000001
    - type: mrr_at_1
      value: 47.678
    - type: mrr_at_10
      value: 56.257000000000005
    - type: mrr_at_100
      value: 56.708000000000006
    - type: mrr_at_1000
      value: 56.751
    - type: mrr_at_3
      value: 54.128
    - type: mrr_at_5
      value: 55.181000000000004
    - type: ndcg_at_1
      value: 45.511
    - type: ndcg_at_10
      value: 35.867
    - type: ndcg_at_100
      value: 31.566
    - type: ndcg_at_1000
      value: 40.077
    - type: ndcg_at_3
      value: 41.9
    - type: ndcg_at_5
      value: 39.367999999999995
    - type: precision_at_1
      value: 47.678
    - type: precision_at_10
      value: 26.842
    - type: precision_at_100
      value: 7.991
    - type: precision_at_1000
      value: 2.0469999999999997
    - type: precision_at_3
      value: 39.938
    - type: precision_at_5
      value: 34.613
    - type: recall_at_1
      value: 5.6770000000000005
    - type: recall_at_10
      value: 17.119999999999997
    - type: recall_at_100
      value: 30.828
    - type: recall_at_1000
      value: 62.082
    - type: recall_at_3
      value: 10.456
    - type: recall_at_5
      value: 12.903999999999998
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: mteb/nq
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 39.021
    - type: map_at_10
      value: 54.976
    - type: map_at_100
      value: 55.793000000000006
    - type: map_at_1000
      value: 55.811
    - type: map_at_3
      value: 50.759
    - type: map_at_5
      value: 53.429
    - type: mrr_at_1
      value: 43.308
    - type: mrr_at_10
      value: 57.118
    - type: mrr_at_100
      value: 57.69499999999999
    - type: mrr_at_1000
      value: 57.704
    - type: mrr_at_3
      value: 53.848
    - type: mrr_at_5
      value: 55.915000000000006
    - type: ndcg_at_1
      value: 43.308
    - type: ndcg_at_10
      value: 62.33800000000001
    - type: ndcg_at_100
      value: 65.61099999999999
    - type: ndcg_at_1000
      value: 65.995
    - type: ndcg_at_3
      value: 54.723
    - type: ndcg_at_5
      value: 59.026
    - type: precision_at_1
      value: 43.308
    - type: precision_at_10
      value: 9.803
    - type: precision_at_100
      value: 1.167
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_3
      value: 24.334
    - type: precision_at_5
      value: 17.144000000000002
    - type: recall_at_1
      value: 39.021
    - type: recall_at_10
      value: 82.37299999999999
    - type: recall_at_100
      value: 96.21499999999999
    - type: recall_at_1000
      value: 99.02499999999999
    - type: recall_at_3
      value: 63.031000000000006
    - type: recall_at_5
      value: 72.856
  - task:
      type: Classification
    dataset:
      name: MTEB NewsClassification
      type: ag_news
      config: default
      split: test
      revision: eb185aade064a813bc0b7f42de02595523103ca4
    metrics:
    - type: accuracy
      value: 78.03289473684211
    - type: f1
      value: 77.89323745730803
  - 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: 100.0
    - type: cos_sim_f1
      value: 99.9490575649516
    - type: cos_sim_precision
      value: 100.0
    - type: cos_sim_recall
      value: 99.89816700610999
    - type: dot_accuracy
      value: 99.89816700610999
    - type: dot_ap
      value: 100.0
    - type: dot_f1
      value: 99.9490575649516
    - type: dot_precision
      value: 100.0
    - type: dot_recall
      value: 99.89816700610999
    - type: euclidean_accuracy
      value: 99.89816700610999
    - type: euclidean_ap
      value: 100.0
    - type: euclidean_f1
      value: 99.9490575649516
    - type: euclidean_precision
      value: 100.0
    - type: euclidean_recall
      value: 99.89816700610999
    - type: manhattan_accuracy
      value: 99.89816700610999
    - type: manhattan_ap
      value: 100.0
    - type: manhattan_f1
      value: 99.9490575649516
    - type: manhattan_precision
      value: 100.0
    - type: manhattan_recall
      value: 99.89816700610999
    - type: max_accuracy
      value: 99.89816700610999
    - type: max_ap
      value: 100.0
    - 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: 61.75000000000001
    - type: cos_sim_ap
      value: 59.578879568280385
    - type: cos_sim_f1
      value: 62.50861474844934
    - type: cos_sim_precision
      value: 45.46365914786967
    - type: cos_sim_recall
      value: 100.0
    - type: dot_accuracy
      value: 61.75000000000001
    - type: dot_ap
      value: 59.57893088951573
    - type: dot_f1
      value: 62.50861474844934
    - type: dot_precision
      value: 45.46365914786967
    - type: dot_recall
      value: 100.0
    - type: euclidean_accuracy
      value: 61.75000000000001
    - type: euclidean_ap
      value: 59.578755624671686
    - type: euclidean_f1
      value: 62.50861474844934
    - type: euclidean_precision
      value: 45.46365914786967
    - type: euclidean_recall
      value: 100.0
    - type: manhattan_accuracy
      value: 61.75000000000001
    - type: manhattan_ap
      value: 59.58504334461159
    - type: manhattan_f1
      value: 62.50861474844934
    - type: manhattan_precision
      value: 45.46365914786967
    - type: manhattan_recall
      value: 100.0
    - type: max_accuracy
      value: 61.75000000000001
    - type: max_ap
      value: 59.58504334461159
    - type: max_f1
      value: 62.50861474844934
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: mteb/quora
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
    - type: map_at_1
      value: 70.186
    - type: map_at_10
      value: 83.875
    - type: map_at_100
      value: 84.514
    - type: map_at_1000
      value: 84.53500000000001
    - type: map_at_3
      value: 80.926
    - type: map_at_5
      value: 82.797
    - type: mrr_at_1
      value: 80.82000000000001
    - type: mrr_at_10
      value: 87.068
    - type: mrr_at_100
      value: 87.178
    - type: mrr_at_1000
      value: 87.18
    - type: mrr_at_3
      value: 86.055
    - type: mrr_at_5
      value: 86.763
    - type: ndcg_at_1
      value: 80.84
    - type: ndcg_at_10
      value: 87.723
    - type: ndcg_at_100
      value: 88.98700000000001
    - type: ndcg_at_1000
      value: 89.13499999999999
    - type: ndcg_at_3
      value: 84.821
    - type: ndcg_at_5
      value: 86.441
    - type: precision_at_1
      value: 80.84
    - type: precision_at_10
      value: 13.270000000000001
    - type: precision_at_100
      value: 1.516
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 37.013
    - type: precision_at_5
      value: 24.37
    - type: recall_at_1
      value: 70.186
    - type: recall_at_10
      value: 94.948
    - type: recall_at_100
      value: 99.223
    - type: recall_at_1000
      value: 99.932
    - type: recall_at_3
      value: 86.57000000000001
    - type: recall_at_5
      value: 91.157
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 50.24198927949519
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
    metrics:
    - type: v_measure
      value: 61.452073078765544
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: mteb/scidocs
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
    metrics:
    - type: map_at_1
      value: 4.972
    - type: map_at_10
      value: 12.314
    - type: map_at_100
      value: 14.333000000000002
    - type: map_at_1000
      value: 14.628
    - type: map_at_3
      value: 8.972
    - type: map_at_5
      value: 10.724
    - type: mrr_at_1
      value: 24.4
    - type: mrr_at_10
      value: 35.257
    - type: mrr_at_100
      value: 36.297000000000004
    - type: mrr_at_1000
      value: 36.363
    - type: mrr_at_3
      value: 32.267
    - type: mrr_at_5
      value: 33.942
    - type: ndcg_at_1
      value: 24.4
    - type: ndcg_at_10
      value: 20.47
    - type: ndcg_at_100
      value: 28.111000000000004
    - type: ndcg_at_1000
      value: 33.499
    - type: ndcg_at_3
      value: 19.975
    - type: ndcg_at_5
      value: 17.293
    - type: precision_at_1
      value: 24.4
    - type: precision_at_10
      value: 10.440000000000001
    - type: precision_at_100
      value: 2.136
    - type: precision_at_1000
      value: 0.34299999999999997
    - type: precision_at_3
      value: 18.733
    - type: precision_at_5
      value: 15.120000000000001
    - type: recall_at_1
      value: 4.972
    - type: recall_at_10
      value: 21.157
    - type: recall_at_100
      value: 43.335
    - type: recall_at_1000
      value: 69.652
    - type: recall_at_3
      value: 11.417
    - type: recall_at_5
      value: 15.317
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cos_sim_pearson
      value: 76.70295978506286
    - type: cos_sim_spearman
      value: 70.91162732446628
    - type: euclidean_pearson
      value: 73.25693688746031
    - type: euclidean_spearman
      value: 70.91162556180127
    - type: manhattan_pearson
      value: 73.27735004735767
    - type: manhattan_spearman
      value: 70.8856787022704
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 67.55878682646774
    - type: cos_sim_spearman
      value: 66.10824660353681
    - type: euclidean_pearson
      value: 64.93937270068541
    - type: euclidean_spearman
      value: 66.10824660353681
    - type: manhattan_pearson
      value: 64.96325555978984
    - type: manhattan_spearman
      value: 66.12052481638577
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 79.79979774019496
    - type: cos_sim_spearman
      value: 79.82293444619499
    - type: euclidean_pearson
      value: 79.4830436509311
    - type: euclidean_spearman
      value: 79.82293444619499
    - type: manhattan_pearson
      value: 79.49785594799296
    - type: manhattan_spearman
      value: 79.8280390479434
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 76.36839628231121
    - type: cos_sim_spearman
      value: 73.63809739428072
    - type: euclidean_pearson
      value: 74.93718121215906
    - type: euclidean_spearman
      value: 73.63810227650436
    - type: manhattan_pearson
      value: 74.8737197659424
    - type: manhattan_spearman
      value: 73.57534688126572
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 82.67482138157656
    - type: cos_sim_spearman
      value: 83.23485786963107
    - type: euclidean_pearson
      value: 82.50847772197369
    - type: euclidean_spearman
      value: 83.23485786963107
    - type: manhattan_pearson
      value: 82.48916218377576
    - type: manhattan_spearman
      value: 83.19756483500014
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 81.11626268793967
    - type: cos_sim_spearman
      value: 81.58184691061507
    - type: euclidean_pearson
      value: 80.65900869004938
    - type: euclidean_spearman
      value: 81.58184691061507
    - type: manhattan_pearson
      value: 80.67912306966772
    - type: manhattan_spearman
      value: 81.59957593393145
  - 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: 80.3140990821409
    - type: cos_sim_spearman
      value: 80.59196586367551
    - type: euclidean_pearson
      value: 80.73014029317672
    - type: euclidean_spearman
      value: 80.59196586367551
    - type: manhattan_pearson
      value: 80.5774325136987
    - type: manhattan_spearman
      value: 80.35102610546238
  - 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: 68.34450491529164
    - type: cos_sim_spearman
      value: 68.79451793414492
    - type: euclidean_pearson
      value: 68.75619738499324
    - type: euclidean_spearman
      value: 68.79451793414492
    - type: manhattan_pearson
      value: 68.75256119543882
    - type: manhattan_spearman
      value: 68.81836416978547
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 77.95580414975612
    - type: cos_sim_spearman
      value: 77.89671867168987
    - type: euclidean_pearson
      value: 77.61352097720862
    - type: euclidean_spearman
      value: 77.89671867168987
    - type: manhattan_pearson
      value: 77.65282228135632
    - type: manhattan_spearman
      value: 77.91730533156762
  - 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: 77.95580421496413
    - type: cos_sim_spearman
      value: 77.89671867168987
    - type: euclidean_pearson
      value: 77.61352107168794
    - type: euclidean_spearman
      value: 77.89671867168987
    - type: manhattan_pearson
      value: 77.65282237231794
    - type: manhattan_spearman
      value: 77.91730533156762
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 79.22928110092924
    - type: mrr
      value: 94.46700902583257
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 56.011
    - type: map_at_10
      value: 65.544
    - type: map_at_100
      value: 66.034
    - type: map_at_1000
      value: 66.065
    - type: map_at_3
      value: 63.077000000000005
    - type: map_at_5
      value: 64.354
    - type: mrr_at_1
      value: 59.0
    - type: mrr_at_10
      value: 66.74900000000001
    - type: mrr_at_100
      value: 67.176
    - type: mrr_at_1000
      value: 67.203
    - type: mrr_at_3
      value: 65.056
    - type: mrr_at_5
      value: 65.956
    - type: ndcg_at_1
      value: 59.0
    - type: ndcg_at_10
      value: 69.95599999999999
    - type: ndcg_at_100
      value: 72.27
    - type: ndcg_at_1000
      value: 73.066
    - type: ndcg_at_3
      value: 65.837
    - type: ndcg_at_5
      value: 67.633
    - type: precision_at_1
      value: 59.0
    - type: precision_at_10
      value: 9.333
    - type: precision_at_100
      value: 1.053
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 26.0
    - type: precision_at_5
      value: 16.866999999999997
    - type: recall_at_1
      value: 56.011
    - type: recall_at_10
      value: 82.133
    - type: recall_at_100
      value: 92.767
    - type: recall_at_1000
      value: 99.0
    - type: recall_at_3
      value: 70.95
    - type: recall_at_5
      value: 75.556
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cos_sim_accuracy
      value: 99.81584158415842
    - type: cos_sim_ap
      value: 94.67482871230736
    - type: cos_sim_f1
      value: 90.67201604814443
    - type: cos_sim_precision
      value: 90.94567404426559
    - type: cos_sim_recall
      value: 90.4
    - type: dot_accuracy
      value: 99.81584158415842
    - type: dot_ap
      value: 94.67482871230737
    - type: dot_f1
      value: 90.67201604814443
    - type: dot_precision
      value: 90.94567404426559
    - type: dot_recall
      value: 90.4
    - type: euclidean_accuracy
      value: 99.81584158415842
    - type: euclidean_ap
      value: 94.67482871230737
    - type: euclidean_f1
      value: 90.67201604814443
    - type: euclidean_precision
      value: 90.94567404426559
    - type: euclidean_recall
      value: 90.4
    - type: manhattan_accuracy
      value: 99.81188118811882
    - type: manhattan_ap
      value: 94.6409082219286
    - type: manhattan_f1
      value: 90.50949050949052
    - type: manhattan_precision
      value: 90.41916167664671
    - type: manhattan_recall
      value: 90.60000000000001
    - type: max_accuracy
      value: 99.81584158415842
    - type: max_ap
      value: 94.67482871230737
    - type: max_f1
      value: 90.67201604814443
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 62.63494511649264
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 37.165838327685755
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 51.384873075208084
    - type: mrr
      value: 52.196439181733304
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 32.13690355567596
    - type: cos_sim_spearman
      value: 31.38349778638125
    - type: dot_pearson
      value: 32.13689596691593
    - type: dot_spearman
      value: 31.38349778638125
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: mteb/trec-covid
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
    metrics:
    - type: map_at_1
      value: 0.26
    - type: map_at_10
      value: 2.08
    - type: map_at_100
      value: 12.598
    - type: map_at_1000
      value: 30.119
    - type: map_at_3
      value: 0.701
    - type: map_at_5
      value: 1.11
    - type: mrr_at_1
      value: 96.0
    - type: mrr_at_10
      value: 97.167
    - type: mrr_at_100
      value: 97.167
    - type: mrr_at_1000
      value: 97.167
    - type: mrr_at_3
      value: 96.667
    - type: mrr_at_5
      value: 97.167
    - type: ndcg_at_1
      value: 91.0
    - type: ndcg_at_10
      value: 81.69800000000001
    - type: ndcg_at_100
      value: 62.9
    - type: ndcg_at_1000
      value: 55.245999999999995
    - type: ndcg_at_3
      value: 86.397
    - type: ndcg_at_5
      value: 84.286
    - type: precision_at_1
      value: 96.0
    - type: precision_at_10
      value: 87.0
    - type: precision_at_100
      value: 64.86
    - type: precision_at_1000
      value: 24.512
    - type: precision_at_3
      value: 90.667
    - type: precision_at_5
      value: 88.8
    - type: recall_at_1
      value: 0.26
    - type: recall_at_10
      value: 2.238
    - type: recall_at_100
      value: 15.488
    - type: recall_at_1000
      value: 51.6
    - type: recall_at_3
      value: 0.716
    - type: recall_at_5
      value: 1.151
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: mteb/touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 3.376
    - type: map_at_10
      value: 13.142000000000001
    - type: map_at_100
      value: 19.763
    - type: map_at_1000
      value: 21.319
    - type: map_at_3
      value: 6.805999999999999
    - type: map_at_5
      value: 8.952
    - type: mrr_at_1
      value: 46.939
    - type: mrr_at_10
      value: 61.082
    - type: mrr_at_100
      value: 61.45
    - type: mrr_at_1000
      value: 61.468999999999994
    - type: mrr_at_3
      value: 57.483
    - type: mrr_at_5
      value: 59.931999999999995
    - type: ndcg_at_1
      value: 44.897999999999996
    - type: ndcg_at_10
      value: 32.35
    - type: ndcg_at_100
      value: 42.719
    - type: ndcg_at_1000
      value: 53.30200000000001
    - type: ndcg_at_3
      value: 37.724999999999994
    - type: ndcg_at_5
      value: 34.79
    - type: precision_at_1
      value: 46.939
    - type: precision_at_10
      value: 28.366999999999997
    - type: precision_at_100
      value: 8.429
    - type: precision_at_1000
      value: 1.557
    - type: precision_at_3
      value: 38.095
    - type: precision_at_5
      value: 33.469
    - type: recall_at_1
      value: 3.376
    - type: recall_at_10
      value: 20.164
    - type: recall_at_100
      value: 50.668
    - type: recall_at_1000
      value: 83.159
    - type: recall_at_3
      value: 8.155
    - type: recall_at_5
      value: 11.872
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 66.739
    - type: ap
      value: 12.17931839228834
    - type: f1
      value: 51.05383188624636
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 56.72891907187323
    - type: f1
      value: 56.997614557150946
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 39.825318429345224
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 83.65619598259522
    - type: cos_sim_ap
      value: 66.17412885183877
    - type: cos_sim_f1
      value: 63.09125656951745
    - type: cos_sim_precision
      value: 57.63858577040594
    - type: cos_sim_recall
      value: 69.68337730870712
    - type: dot_accuracy
      value: 83.65619598259522
    - type: dot_ap
      value: 66.17413621964548
    - type: dot_f1
      value: 63.09125656951745
    - type: dot_precision
      value: 57.63858577040594
    - type: dot_recall
      value: 69.68337730870712
    - type: euclidean_accuracy
      value: 83.65619598259522
    - type: euclidean_ap
      value: 66.17412836413126
    - type: euclidean_f1
      value: 63.09125656951745
    - type: euclidean_precision
      value: 57.63858577040594
    - type: euclidean_recall
      value: 69.68337730870712
    - type: manhattan_accuracy
      value: 83.5548667819038
    - type: manhattan_ap
      value: 66.07998834521334
    - type: manhattan_f1
      value: 62.96433419721092
    - type: manhattan_precision
      value: 59.14676559239509
    - type: manhattan_recall
      value: 67.30870712401055
    - type: max_accuracy
      value: 83.65619598259522
    - type: max_ap
      value: 66.17413621964548
    - type: max_f1
      value: 63.09125656951745
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.55706911941631
    - type: cos_sim_ap
      value: 85.20971331546805
    - type: cos_sim_f1
      value: 77.28446050593702
    - type: cos_sim_precision
      value: 74.16135881104033
    - type: cos_sim_recall
      value: 80.6821681552202
    - type: dot_accuracy
      value: 88.55706911941631
    - type: dot_ap
      value: 85.2097154112633
    - type: dot_f1
      value: 77.28446050593702
    - type: dot_precision
      value: 74.16135881104033
    - type: dot_recall
      value: 80.6821681552202
    - type: euclidean_accuracy
      value: 88.55706911941631
    - type: euclidean_ap
      value: 85.20971719214488
    - type: euclidean_f1
      value: 77.28446050593702
    - type: euclidean_precision
      value: 74.16135881104033
    - type: euclidean_recall
      value: 80.6821681552202
    - type: manhattan_accuracy
      value: 88.52020025614158
    - type: manhattan_ap
      value: 85.17569799117058
    - type: manhattan_f1
      value: 77.27157773040933
    - type: manhattan_precision
      value: 72.79286638077734
    - type: manhattan_recall
      value: 82.33754234678165
    - type: max_accuracy
      value: 88.55706911941631
    - type: max_ap
      value: 85.20971719214488
    - type: max_f1
      value: 77.28446050593702
  - task:
      type: Clustering
    dataset:
      name: MTEB WikiCitiesClustering
      type: jinaai/cities_wiki_clustering
      config: default
      split: test
      revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
    metrics:
    - type: v_measure
      value: 85.63474850264893
---

# yixuan-chia/snowflake-arctic-embed-m-long-Q8_0-GGUF
This model was converted to GGUF format from [`Snowflake/snowflake-arctic-embed-m-long`](https://huggingface.co/Snowflake/snowflake-arctic-embed-m-long) 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-m-long) 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 yixuan-chia/snowflake-arctic-embed-m-long-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-long-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo yixuan-chia/snowflake-arctic-embed-m-long-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-long-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 yixuan-chia/snowflake-arctic-embed-m-long-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-long-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo yixuan-chia/snowflake-arctic-embed-m-long-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-long-q8_0.gguf -c 2048
```
