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-s base_model:quantized:Snowflake/snowflake-arctic-embed-s license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
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
```
