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-l base_model:quantized:Snowflake/snowflake-arctic-embed-l license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: Snowflake/snowflake-arctic-embed-l
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-embed-l
  results:
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonCounterfactualClassification (en)
      type: mteb/amazon_counterfactual
      config: en
      split: test
      revision: e8379541af4e31359cca9fbcf4b00f2671dba205
    metrics:
    - type: accuracy
      value: 74.80597014925374
    - type: ap
      value: 37.911466766189875
    - type: f1
      value: 68.88606927542106
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonPolarityClassification
      type: mteb/amazon_polarity
      config: default
      split: test
      revision: e2d317d38cd51312af73b3d32a06d1a08b442046
    metrics:
    - type: accuracy
      value: 78.402275
    - type: ap
      value: 73.03294793248114
    - type: f1
      value: 78.3147786132161
  - task:
      type: Classification
    dataset:
      name: MTEB AmazonReviewsClassification (en)
      type: mteb/amazon_reviews_multi
      config: en
      split: test
      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
    metrics:
    - type: accuracy
      value: 36.717999999999996
    - type: f1
      value: 35.918044248787766
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguAna
      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
    metrics:
    - type: map_at_1
      value: 34.495
    - type: map_at_10
      value: 50.236000000000004
    - type: map_at_100
      value: 50.944
    - type: map_at_1000
      value: 50.94499999999999
    - type: map_at_3
      value: 45.341
    - type: map_at_5
      value: 48.286
    - type: mrr_at_1
      value: 35.135
    - type: mrr_at_10
      value: 50.471
    - type: mrr_at_100
      value: 51.185
    - type: mrr_at_1000
      value: 51.187000000000005
    - type: mrr_at_3
      value: 45.602
    - type: mrr_at_5
      value: 48.468
    - type: ndcg_at_1
      value: 34.495
    - type: ndcg_at_10
      value: 59.086000000000006
    - type: ndcg_at_100
      value: 61.937
    - type: ndcg_at_1000
      value: 61.966
    - type: ndcg_at_3
      value: 49.062
    - type: ndcg_at_5
      value: 54.367
    - type: precision_at_1
      value: 34.495
    - type: precision_at_10
      value: 8.734
    - type: precision_at_100
      value: 0.9939999999999999
    - type: precision_at_1000
      value: 0.1
    - type: precision_at_3
      value: 19.962
    - type: precision_at_5
      value: 14.552000000000001
    - type: recall_at_1
      value: 34.495
    - type: recall_at_10
      value: 87.33999999999999
    - type: recall_at_100
      value: 99.431
    - type: recall_at_1000
      value: 99.644
    - type: recall_at_3
      value: 59.885999999999996
    - type: recall_at_5
      value: 72.76
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringP2P
      type: mteb/arxiv-clustering-p2p
      config: default
      split: test
      revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d
    metrics:
    - type: v_measure
      value: 47.46440874635501
  - task:
      type: Clustering
    dataset:
      name: MTEB ArxivClusteringS2S
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: v_measure
      value: 38.28720154213723
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: map
      value: 60.34614226394902
    - type: mrr
      value: 75.05628105351096
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cos_sim_pearson
      value: 87.41072716728198
    - type: cos_sim_spearman
      value: 86.34534093114372
    - type: euclidean_pearson
      value: 85.34009667750838
    - type: euclidean_spearman
      value: 86.34534093114372
    - type: manhattan_pearson
      value: 85.2158833586889
    - type: manhattan_spearman
      value: 86.60920236509224
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 80.06493506493507
    - type: f1
      value: 79.28108600339833
  - task:
      type: Clustering
    dataset:
      name: MTEB BigPatentClustering
      type: jinaai/big-patent-clustering
      config: default
      split: test
      revision: 62d5330920bca426ce9d3c76ea914f15fc83e891
    metrics:
    - type: v_measure
      value: 20.545049432417287
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: v_measure
      value: 37.54369718479804
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: v_measure
      value: 32.64941588219162
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: mteb/cqadupstack-android
      config: default
      split: test
      revision: f46a197baaae43b4f621051089b82a364682dfeb
    metrics:
    - type: map_at_1
      value: 37.264
    - type: map_at_10
      value: 49.43
    - type: map_at_100
      value: 50.967
    - type: map_at_1000
      value: 51.08200000000001
    - type: map_at_3
      value: 45.742
    - type: map_at_5
      value: 47.764
    - type: mrr_at_1
      value: 44.921
    - type: mrr_at_10
      value: 54.879999999999995
    - type: mrr_at_100
      value: 55.525000000000006
    - type: mrr_at_1000
      value: 55.565
    - type: mrr_at_3
      value: 52.480000000000004
    - type: mrr_at_5
      value: 53.86
    - type: ndcg_at_1
      value: 44.921
    - type: ndcg_at_10
      value: 55.664
    - type: ndcg_at_100
      value: 60.488
    - type: ndcg_at_1000
      value: 62.138000000000005
    - type: ndcg_at_3
      value: 50.797000000000004
    - type: ndcg_at_5
      value: 52.94799999999999
    - type: precision_at_1
      value: 44.921
    - type: precision_at_10
      value: 10.587
    - type: precision_at_100
      value: 1.629
    - type: precision_at_1000
      value: 0.203
    - type: precision_at_3
      value: 24.034
    - type: precision_at_5
      value: 17.224999999999998
    - type: recall_at_1
      value: 37.264
    - type: recall_at_10
      value: 67.15
    - type: recall_at_100
      value: 86.811
    - type: recall_at_1000
      value: 97.172
    - type: recall_at_3
      value: 53.15800000000001
    - type: recall_at_5
      value: 59.116
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: mteb/cqadupstack-english
      config: default
      split: test
      revision: ad9991cb51e31e31e430383c75ffb2885547b5f0
    metrics:
    - type: map_at_1
      value: 36.237
    - type: map_at_10
      value: 47.941
    - type: map_at_100
      value: 49.131
    - type: map_at_1000
      value: 49.26
    - type: map_at_3
      value: 44.561
    - type: map_at_5
      value: 46.28
    - type: mrr_at_1
      value: 45.605000000000004
    - type: mrr_at_10
      value: 54.039
    - type: mrr_at_100
      value: 54.653
    - type: mrr_at_1000
      value: 54.688
    - type: mrr_at_3
      value: 52.006
    - type: mrr_at_5
      value: 53.096
    - type: ndcg_at_1
      value: 45.605000000000004
    - type: ndcg_at_10
      value: 53.916
    - type: ndcg_at_100
      value: 57.745999999999995
    - type: ndcg_at_1000
      value: 59.492999999999995
    - type: ndcg_at_3
      value: 49.774
    - type: ndcg_at_5
      value: 51.434999999999995
    - type: precision_at_1
      value: 45.605000000000004
    - type: precision_at_10
      value: 10.229000000000001
    - type: precision_at_100
      value: 1.55
    - type: precision_at_1000
      value: 0.2
    - type: precision_at_3
      value: 24.098
    - type: precision_at_5
      value: 16.726
    - type: recall_at_1
      value: 36.237
    - type: recall_at_10
      value: 64.03
    - type: recall_at_100
      value: 80.423
    - type: recall_at_1000
      value: 91.03
    - type: recall_at_3
      value: 51.20400000000001
    - type: recall_at_5
      value: 56.298
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: mteb/cqadupstack-gaming
      config: default
      split: test
      revision: 4885aa143210c98657558c04aaf3dc47cfb54340
    metrics:
    - type: map_at_1
      value: 47.278
    - type: map_at_10
      value: 59.757000000000005
    - type: map_at_100
      value: 60.67
    - type: map_at_1000
      value: 60.714
    - type: map_at_3
      value: 56.714
    - type: map_at_5
      value: 58.453
    - type: mrr_at_1
      value: 53.73
    - type: mrr_at_10
      value: 62.970000000000006
    - type: mrr_at_100
      value: 63.507999999999996
    - type: mrr_at_1000
      value: 63.53
    - type: mrr_at_3
      value: 60.909
    - type: mrr_at_5
      value: 62.172000000000004
    - type: ndcg_at_1
      value: 53.73
    - type: ndcg_at_10
      value: 64.97
    - type: ndcg_at_100
      value: 68.394
    - type: ndcg_at_1000
      value: 69.255
    - type: ndcg_at_3
      value: 60.228
    - type: ndcg_at_5
      value: 62.617999999999995
    - type: precision_at_1
      value: 53.73
    - type: precision_at_10
      value: 10.056
    - type: precision_at_100
      value: 1.265
    - type: precision_at_1000
      value: 0.13699999999999998
    - type: precision_at_3
      value: 26.332
    - type: precision_at_5
      value: 17.743000000000002
    - type: recall_at_1
      value: 47.278
    - type: recall_at_10
      value: 76.86500000000001
    - type: recall_at_100
      value: 91.582
    - type: recall_at_1000
      value: 97.583
    - type: recall_at_3
      value: 64.443
    - type: recall_at_5
      value: 70.283
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: mteb/cqadupstack-gis
      config: default
      split: test
      revision: 5003b3064772da1887988e05400cf3806fe491f2
    metrics:
    - type: map_at_1
      value: 29.702
    - type: map_at_10
      value: 39.463
    - type: map_at_100
      value: 40.508
    - type: map_at_1000
      value: 40.579
    - type: map_at_3
      value: 36.748999999999995
    - type: map_at_5
      value: 38.296
    - type: mrr_at_1
      value: 31.977
    - type: mrr_at_10
      value: 41.739
    - type: mrr_at_100
      value: 42.586
    - type: mrr_at_1000
      value: 42.636
    - type: mrr_at_3
      value: 39.096
    - type: mrr_at_5
      value: 40.695
    - type: ndcg_at_1
      value: 31.977
    - type: ndcg_at_10
      value: 44.855000000000004
    - type: ndcg_at_100
      value: 49.712
    - type: ndcg_at_1000
      value: 51.443000000000005
    - type: ndcg_at_3
      value: 39.585
    - type: ndcg_at_5
      value: 42.244
    - type: precision_at_1
      value: 31.977
    - type: precision_at_10
      value: 6.768000000000001
    - type: precision_at_100
      value: 0.9690000000000001
    - type: precision_at_1000
      value: 0.116
    - type: precision_at_3
      value: 16.761
    - type: precision_at_5
      value: 11.593
    - type: recall_at_1
      value: 29.702
    - type: recall_at_10
      value: 59.082
    - type: recall_at_100
      value: 80.92
    - type: recall_at_1000
      value: 93.728
    - type: recall_at_3
      value: 45.212
    - type: recall_at_5
      value: 51.449
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: mteb/cqadupstack-mathematica
      config: default
      split: test
      revision: 90fceea13679c63fe563ded68f3b6f06e50061de
    metrics:
    - type: map_at_1
      value: 21.336
    - type: map_at_10
      value: 30.137999999999998
    - type: map_at_100
      value: 31.385
    - type: map_at_1000
      value: 31.495
    - type: map_at_3
      value: 27.481
    - type: map_at_5
      value: 28.772
    - type: mrr_at_1
      value: 25.871
    - type: mrr_at_10
      value: 34.686
    - type: mrr_at_100
      value: 35.649
    - type: mrr_at_1000
      value: 35.705
    - type: mrr_at_3
      value: 32.09
    - type: mrr_at_5
      value: 33.52
    - type: ndcg_at_1
      value: 25.871
    - type: ndcg_at_10
      value: 35.617
    - type: ndcg_at_100
      value: 41.272999999999996
    - type: ndcg_at_1000
      value: 43.725
    - type: ndcg_at_3
      value: 30.653999999999996
    - type: ndcg_at_5
      value: 32.714
    - type: precision_at_1
      value: 25.871
    - type: precision_at_10
      value: 6.4799999999999995
    - type: precision_at_100
      value: 1.0699999999999998
    - type: precision_at_1000
      value: 0.13999999999999999
    - type: precision_at_3
      value: 14.469000000000001
    - type: precision_at_5
      value: 10.274
    - type: recall_at_1
      value: 21.336
    - type: recall_at_10
      value: 47.746
    - type: recall_at_100
      value: 71.773
    - type: recall_at_1000
      value: 89.05199999999999
    - type: recall_at_3
      value: 34.172999999999995
    - type: recall_at_5
      value: 39.397999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: mteb/cqadupstack-physics
      config: default
      split: test
      revision: 79531abbd1fb92d06c6d6315a0cbbbf5bb247ea4
    metrics:
    - type: map_at_1
      value: 34.424
    - type: map_at_10
      value: 45.647999999999996
    - type: map_at_100
      value: 46.907
    - type: map_at_1000
      value: 47.010999999999996
    - type: map_at_3
      value: 42.427
    - type: map_at_5
      value: 44.285000000000004
    - type: mrr_at_1
      value: 41.867
    - type: mrr_at_10
      value: 51.17699999999999
    - type: mrr_at_100
      value: 51.937
    - type: mrr_at_1000
      value: 51.975
    - type: mrr_at_3
      value: 48.941
    - type: mrr_at_5
      value: 50.322
    - type: ndcg_at_1
      value: 41.867
    - type: ndcg_at_10
      value: 51.534
    - type: ndcg_at_100
      value: 56.696999999999996
    - type: ndcg_at_1000
      value: 58.475
    - type: ndcg_at_3
      value: 46.835
    - type: ndcg_at_5
      value: 49.161
    - type: precision_at_1
      value: 41.867
    - type: precision_at_10
      value: 9.134
    - type: precision_at_100
      value: 1.362
    - type: precision_at_1000
      value: 0.17099999999999999
    - type: precision_at_3
      value: 22.073
    - type: precision_at_5
      value: 15.495999999999999
    - type: recall_at_1
      value: 34.424
    - type: recall_at_10
      value: 63.237
    - type: recall_at_100
      value: 84.774
    - type: recall_at_1000
      value: 95.987
    - type: recall_at_3
      value: 49.888
    - type: recall_at_5
      value: 55.940999999999995
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: mteb/cqadupstack-programmers
      config: default
      split: test
      revision: 6184bc1440d2dbc7612be22b50686b8826d22b32
    metrics:
    - type: map_at_1
      value: 30.72
    - type: map_at_10
      value: 41.327999999999996
    - type: map_at_100
      value: 42.651
    - type: map_at_1000
      value: 42.739
    - type: map_at_3
      value: 38.223
    - type: map_at_5
      value: 40.053
    - type: mrr_at_1
      value: 37.9
    - type: mrr_at_10
      value: 46.857
    - type: mrr_at_100
      value: 47.673
    - type: mrr_at_1000
      value: 47.711999999999996
    - type: mrr_at_3
      value: 44.292
    - type: mrr_at_5
      value: 45.845
    - type: ndcg_at_1
      value: 37.9
    - type: ndcg_at_10
      value: 47.105999999999995
    - type: ndcg_at_100
      value: 52.56999999999999
    - type: ndcg_at_1000
      value: 54.37800000000001
    - type: ndcg_at_3
      value: 42.282
    - type: ndcg_at_5
      value: 44.646
    - type: precision_at_1
      value: 37.9
    - type: precision_at_10
      value: 8.368
    - type: precision_at_100
      value: 1.283
    - type: precision_at_1000
      value: 0.16
    - type: precision_at_3
      value: 20.015
    - type: precision_at_5
      value: 14.132
    - type: recall_at_1
      value: 30.72
    - type: recall_at_10
      value: 58.826
    - type: recall_at_100
      value: 82.104
    - type: recall_at_1000
      value: 94.194
    - type: recall_at_3
      value: 44.962999999999994
    - type: recall_at_5
      value: 51.426
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackRetrieval
      type: mteb/cqadupstack
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 31.656583333333334
    - type: map_at_10
      value: 41.59883333333333
    - type: map_at_100
      value: 42.80350000000001
    - type: map_at_1000
      value: 42.91075
    - type: map_at_3
      value: 38.68908333333333
    - type: map_at_5
      value: 40.27733333333334
    - type: mrr_at_1
      value: 37.23483333333334
    - type: mrr_at_10
      value: 45.782000000000004
    - type: mrr_at_100
      value: 46.577083333333334
    - type: mrr_at_1000
      value: 46.62516666666667
    - type: mrr_at_3
      value: 43.480666666666664
    - type: mrr_at_5
      value: 44.79833333333333
    - type: ndcg_at_1
      value: 37.23483333333334
    - type: ndcg_at_10
      value: 46.971500000000006
    - type: ndcg_at_100
      value: 51.90125
    - type: ndcg_at_1000
      value: 53.86366666666667
    - type: ndcg_at_3
      value: 42.31791666666667
    - type: ndcg_at_5
      value: 44.458666666666666
    - type: precision_at_1
      value: 37.23483333333334
    - type: precision_at_10
      value: 8.044583333333332
    - type: precision_at_100
      value: 1.2334166666666666
    - type: precision_at_1000
      value: 0.15925
    - type: precision_at_3
      value: 19.240833333333327
    - type: precision_at_5
      value: 13.435083333333333
    - type: recall_at_1
      value: 31.656583333333334
    - type: recall_at_10
      value: 58.44758333333333
    - type: recall_at_100
      value: 79.93658333333332
    - type: recall_at_1000
      value: 93.32491666666668
    - type: recall_at_3
      value: 45.44266666666667
    - type: recall_at_5
      value: 50.99866666666666
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: mteb/cqadupstack-stats
      config: default
      split: test
      revision: 65ac3a16b8e91f9cee4c9828cc7c335575432a2a
    metrics:
    - type: map_at_1
      value: 28.247
    - type: map_at_10
      value: 35.443999999999996
    - type: map_at_100
      value: 36.578
    - type: map_at_1000
      value: 36.675999999999995
    - type: map_at_3
      value: 33.276
    - type: map_at_5
      value: 34.536
    - type: mrr_at_1
      value: 31.747999999999998
    - type: mrr_at_10
      value: 38.413000000000004
    - type: mrr_at_100
      value: 39.327
    - type: mrr_at_1000
      value: 39.389
    - type: mrr_at_3
      value: 36.401
    - type: mrr_at_5
      value: 37.543
    - type: ndcg_at_1
      value: 31.747999999999998
    - type: ndcg_at_10
      value: 39.646
    - type: ndcg_at_100
      value: 44.861000000000004
    - type: ndcg_at_1000
      value: 47.197
    - type: ndcg_at_3
      value: 35.764
    - type: ndcg_at_5
      value: 37.635999999999996
    - type: precision_at_1
      value: 31.747999999999998
    - type: precision_at_10
      value: 6.12
    - type: precision_at_100
      value: 0.942
    - type: precision_at_1000
      value: 0.123
    - type: precision_at_3
      value: 15.235000000000001
    - type: precision_at_5
      value: 10.491
    - type: recall_at_1
      value: 28.247
    - type: recall_at_10
      value: 49.456
    - type: recall_at_100
      value: 73.02499999999999
    - type: recall_at_1000
      value: 89.898
    - type: recall_at_3
      value: 38.653999999999996
    - type: recall_at_5
      value: 43.259
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: mteb/cqadupstack-tex
      config: default
      split: test
      revision: 46989137a86843e03a6195de44b09deda022eec7
    metrics:
    - type: map_at_1
      value: 22.45
    - type: map_at_10
      value: 30.476999999999997
    - type: map_at_100
      value: 31.630999999999997
    - type: map_at_1000
      value: 31.755
    - type: map_at_3
      value: 27.989000000000004
    - type: map_at_5
      value: 29.410999999999998
    - type: mrr_at_1
      value: 26.979
    - type: mrr_at_10
      value: 34.316
    - type: mrr_at_100
      value: 35.272999999999996
    - type: mrr_at_1000
      value: 35.342
    - type: mrr_at_3
      value: 32.14
    - type: mrr_at_5
      value: 33.405
    - type: ndcg_at_1
      value: 26.979
    - type: ndcg_at_10
      value: 35.166
    - type: ndcg_at_100
      value: 40.583000000000006
    - type: ndcg_at_1000
      value: 43.282
    - type: ndcg_at_3
      value: 30.916
    - type: ndcg_at_5
      value: 32.973
    - type: precision_at_1
      value: 26.979
    - type: precision_at_10
      value: 6.132
    - type: precision_at_100
      value: 1.047
    - type: precision_at_1000
      value: 0.145
    - type: precision_at_3
      value: 14.360999999999999
    - type: precision_at_5
      value: 10.227
    - type: recall_at_1
      value: 22.45
    - type: recall_at_10
      value: 45.348
    - type: recall_at_100
      value: 69.484
    - type: recall_at_1000
      value: 88.628
    - type: recall_at_3
      value: 33.338
    - type: recall_at_5
      value: 38.746
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: mteb/cqadupstack-unix
      config: default
      split: test
      revision: 6c6430d3a6d36f8d2a829195bc5dc94d7e063e53
    metrics:
    - type: map_at_1
      value: 32.123000000000005
    - type: map_at_10
      value: 41.778
    - type: map_at_100
      value: 42.911
    - type: map_at_1000
      value: 42.994
    - type: map_at_3
      value: 38.558
    - type: map_at_5
      value: 40.318
    - type: mrr_at_1
      value: 37.687
    - type: mrr_at_10
      value: 45.889
    - type: mrr_at_100
      value: 46.672999999999995
    - type: mrr_at_1000
      value: 46.72
    - type: mrr_at_3
      value: 43.33
    - type: mrr_at_5
      value: 44.734
    - type: ndcg_at_1
      value: 37.687
    - type: ndcg_at_10
      value: 47.258
    - type: ndcg_at_100
      value: 52.331
    - type: ndcg_at_1000
      value: 54.152
    - type: ndcg_at_3
      value: 41.857
    - type: ndcg_at_5
      value: 44.283
    - type: precision_at_1
      value: 37.687
    - type: precision_at_10
      value: 7.892
    - type: precision_at_100
      value: 1.183
    - type: precision_at_1000
      value: 0.14300000000000002
    - type: precision_at_3
      value: 18.781
    - type: precision_at_5
      value: 13.134
    - type: recall_at_1
      value: 32.123000000000005
    - type: recall_at_10
      value: 59.760000000000005
    - type: recall_at_100
      value: 81.652
    - type: recall_at_1000
      value: 94.401
    - type: recall_at_3
      value: 44.996
    - type: recall_at_5
      value: 51.184
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: mteb/cqadupstack-webmasters
      config: default
      split: test
      revision: 160c094312a0e1facb97e55eeddb698c0abe3571
    metrics:
    - type: map_at_1
      value: 33.196999999999996
    - type: map_at_10
      value: 42.012
    - type: map_at_100
      value: 43.663999999999994
    - type: map_at_1000
      value: 43.883
    - type: map_at_3
      value: 39.33
    - type: map_at_5
      value: 40.586
    - type: mrr_at_1
      value: 39.328
    - type: mrr_at_10
      value: 46.57
    - type: mrr_at_100
      value: 47.508
    - type: mrr_at_1000
      value: 47.558
    - type: mrr_at_3
      value: 44.532
    - type: mrr_at_5
      value: 45.58
    - type: ndcg_at_1
      value: 39.328
    - type: ndcg_at_10
      value: 47.337
    - type: ndcg_at_100
      value: 52.989
    - type: ndcg_at_1000
      value: 55.224
    - type: ndcg_at_3
      value: 43.362
    - type: ndcg_at_5
      value: 44.866
    - type: precision_at_1
      value: 39.328
    - type: precision_at_10
      value: 8.577
    - type: precision_at_100
      value: 1.5789999999999997
    - type: precision_at_1000
      value: 0.25
    - type: precision_at_3
      value: 19.697
    - type: precision_at_5
      value: 13.755
    - type: recall_at_1
      value: 33.196999999999996
    - type: recall_at_10
      value: 56.635000000000005
    - type: recall_at_100
      value: 81.882
    - type: recall_at_1000
      value: 95.342
    - type: recall_at_3
      value: 44.969
    - type: recall_at_5
      value: 49.266
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: mteb/cqadupstack-wordpress
      config: default
      split: test
      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
    metrics:
    - type: map_at_1
      value: 26.901000000000003
    - type: map_at_10
      value: 35.77
    - type: map_at_100
      value: 36.638999999999996
    - type: map_at_1000
      value: 36.741
    - type: map_at_3
      value: 33.219
    - type: map_at_5
      value: 34.574
    - type: mrr_at_1
      value: 29.205
    - type: mrr_at_10
      value: 37.848
    - type: mrr_at_100
      value: 38.613
    - type: mrr_at_1000
      value: 38.682
    - type: mrr_at_3
      value: 35.551
    - type: mrr_at_5
      value: 36.808
    - type: ndcg_at_1
      value: 29.205
    - type: ndcg_at_10
      value: 40.589
    - type: ndcg_at_100
      value: 45.171
    - type: ndcg_at_1000
      value: 47.602
    - type: ndcg_at_3
      value: 35.760999999999996
    - type: ndcg_at_5
      value: 37.980000000000004
    - type: precision_at_1
      value: 29.205
    - type: precision_at_10
      value: 6.192
    - type: precision_at_100
      value: 0.922
    - type: precision_at_1000
      value: 0.123
    - type: precision_at_3
      value: 15.034
    - type: precision_at_5
      value: 10.424999999999999
    - type: recall_at_1
      value: 26.901000000000003
    - type: recall_at_10
      value: 53.236000000000004
    - type: recall_at_100
      value: 74.809
    - type: recall_at_1000
      value: 92.884
    - type: recall_at_3
      value: 40.314
    - type: recall_at_5
      value: 45.617999999999995
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: mteb/climate-fever
      config: default
      split: test
      revision: 47f2ac6acb640fc46020b02a5b59fdda04d39380
    metrics:
    - type: map_at_1
      value: 16.794999999999998
    - type: map_at_10
      value: 29.322
    - type: map_at_100
      value: 31.463
    - type: map_at_1000
      value: 31.643
    - type: map_at_3
      value: 24.517
    - type: map_at_5
      value: 27.237000000000002
    - type: mrr_at_1
      value: 37.655
    - type: mrr_at_10
      value: 50.952
    - type: mrr_at_100
      value: 51.581999999999994
    - type: mrr_at_1000
      value: 51.61
    - type: mrr_at_3
      value: 47.991
    - type: mrr_at_5
      value: 49.744
    - type: ndcg_at_1
      value: 37.655
    - type: ndcg_at_10
      value: 39.328
    - type: ndcg_at_100
      value: 46.358
    - type: ndcg_at_1000
      value: 49.245
    - type: ndcg_at_3
      value: 33.052
    - type: ndcg_at_5
      value: 35.407
    - type: precision_at_1
      value: 37.655
    - type: precision_at_10
      value: 12.202
    - type: precision_at_100
      value: 1.9789999999999999
    - type: precision_at_1000
      value: 0.252
    - type: precision_at_3
      value: 24.973
    - type: precision_at_5
      value: 19.075
    - type: recall_at_1
      value: 16.794999999999998
    - type: recall_at_10
      value: 45.716
    - type: recall_at_100
      value: 68.919
    - type: recall_at_1000
      value: 84.71600000000001
    - type: recall_at_3
      value: 30.135
    - type: recall_at_5
      value: 37.141999999999996
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: mteb/dbpedia
      config: default
      split: test
      revision: c0f706b76e590d620bd6618b3ca8efdd34e2d659
    metrics:
    - type: map_at_1
      value: 9.817
    - type: map_at_10
      value: 22.058
    - type: map_at_100
      value: 31.805
    - type: map_at_1000
      value: 33.562999999999995
    - type: map_at_3
      value: 15.537
    - type: map_at_5
      value: 18.199
    - type: mrr_at_1
      value: 72.75
    - type: mrr_at_10
      value: 79.804
    - type: mrr_at_100
      value: 80.089
    - type: mrr_at_1000
      value: 80.09100000000001
    - type: mrr_at_3
      value: 78.75
    - type: mrr_at_5
      value: 79.325
    - type: ndcg_at_1
      value: 59.875
    - type: ndcg_at_10
      value: 45.972
    - type: ndcg_at_100
      value: 51.092999999999996
    - type: ndcg_at_1000
      value: 58.048
    - type: ndcg_at_3
      value: 50.552
    - type: ndcg_at_5
      value: 47.672
    - type: precision_at_1
      value: 72.75
    - type: precision_at_10
      value: 37.05
    - type: precision_at_100
      value: 12.005
    - type: precision_at_1000
      value: 2.221
    - type: precision_at_3
      value: 54.083000000000006
    - type: precision_at_5
      value: 46.2
    - type: recall_at_1
      value: 9.817
    - type: recall_at_10
      value: 27.877000000000002
    - type: recall_at_100
      value: 57.974000000000004
    - type: recall_at_1000
      value: 80.085
    - type: recall_at_3
      value: 16.911
    - type: recall_at_5
      value: 20.689
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 46.464999999999996
    - type: f1
      value: 42.759588662873796
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: mteb/fever
      config: default
      split: test
      revision: bea83ef9e8fb933d90a2f1d5515737465d613e12
    metrics:
    - type: map_at_1
      value: 75.82900000000001
    - type: map_at_10
      value: 84.613
    - type: map_at_100
      value: 84.845
    - type: map_at_1000
      value: 84.855
    - type: map_at_3
      value: 83.498
    - type: map_at_5
      value: 84.29299999999999
    - type: mrr_at_1
      value: 81.69800000000001
    - type: mrr_at_10
      value: 88.84100000000001
    - type: mrr_at_100
      value: 88.887
    - type: mrr_at_1000
      value: 88.888
    - type: mrr_at_3
      value: 88.179
    - type: mrr_at_5
      value: 88.69200000000001
    - type: ndcg_at_1
      value: 81.69800000000001
    - type: ndcg_at_10
      value: 88.21799999999999
    - type: ndcg_at_100
      value: 88.961
    - type: ndcg_at_1000
      value: 89.131
    - type: ndcg_at_3
      value: 86.591
    - type: ndcg_at_5
      value: 87.666
    - type: precision_at_1
      value: 81.69800000000001
    - type: precision_at_10
      value: 10.615
    - type: precision_at_100
      value: 1.125
    - type: precision_at_1000
      value: 0.11499999999999999
    - type: precision_at_3
      value: 33.208
    - type: precision_at_5
      value: 20.681
    - type: recall_at_1
      value: 75.82900000000001
    - type: recall_at_10
      value: 94.97
    - type: recall_at_100
      value: 97.786
    - type: recall_at_1000
      value: 98.809
    - type: recall_at_3
      value: 90.625
    - type: recall_at_5
      value: 93.345
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: mteb/fiqa
      config: default
      split: test
      revision: 27a168819829fe9bcd655c2df245fb19452e8e06
    metrics:
    - type: map_at_1
      value: 22.788
    - type: map_at_10
      value: 36.71
    - type: map_at_100
      value: 38.527
    - type: map_at_1000
      value: 38.701
    - type: map_at_3
      value: 32.318999999999996
    - type: map_at_5
      value: 34.809
    - type: mrr_at_1
      value: 44.444
    - type: mrr_at_10
      value: 52.868
    - type: mrr_at_100
      value: 53.52400000000001
    - type: mrr_at_1000
      value: 53.559999999999995
    - type: mrr_at_3
      value: 50.153999999999996
    - type: mrr_at_5
      value: 51.651
    - type: ndcg_at_1
      value: 44.444
    - type: ndcg_at_10
      value: 44.707
    - type: ndcg_at_100
      value: 51.174
    - type: ndcg_at_1000
      value: 53.996
    - type: ndcg_at_3
      value: 40.855999999999995
    - type: ndcg_at_5
      value: 42.113
    - type: precision_at_1
      value: 44.444
    - type: precision_at_10
      value: 12.021999999999998
    - type: precision_at_100
      value: 1.8950000000000002
    - type: precision_at_1000
      value: 0.241
    - type: precision_at_3
      value: 26.8
    - type: precision_at_5
      value: 19.66
    - type: recall_at_1
      value: 22.788
    - type: recall_at_10
      value: 51.793
    - type: recall_at_100
      value: 75.69500000000001
    - type: recall_at_1000
      value: 92.292
    - type: recall_at_3
      value: 37.375
    - type: recall_at_5
      value: 43.682
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: mteb/hotpotqa
      config: default
      split: test
      revision: ab518f4d6fcca38d87c25209f94beba119d02014
    metrics:
    - type: map_at_1
      value: 41.276
    - type: map_at_10
      value: 67.245
    - type: map_at_100
      value: 68.061
    - type: map_at_1000
      value: 68.11399999999999
    - type: map_at_3
      value: 63.693
    - type: map_at_5
      value: 65.90899999999999
    - type: mrr_at_1
      value: 82.552
    - type: mrr_at_10
      value: 87.741
    - type: mrr_at_100
      value: 87.868
    - type: mrr_at_1000
      value: 87.871
    - type: mrr_at_3
      value: 86.98599999999999
    - type: mrr_at_5
      value: 87.469
    - type: ndcg_at_1
      value: 82.552
    - type: ndcg_at_10
      value: 75.176
    - type: ndcg_at_100
      value: 77.902
    - type: ndcg_at_1000
      value: 78.852
    - type: ndcg_at_3
      value: 70.30499999999999
    - type: ndcg_at_5
      value: 73.00999999999999
    - type: precision_at_1
      value: 82.552
    - type: precision_at_10
      value: 15.765
    - type: precision_at_100
      value: 1.788
    - type: precision_at_1000
      value: 0.191
    - type: precision_at_3
      value: 45.375
    - type: precision_at_5
      value: 29.360999999999997
    - type: recall_at_1
      value: 41.276
    - type: recall_at_10
      value: 78.825
    - type: recall_at_100
      value: 89.41900000000001
    - type: recall_at_1000
      value: 95.625
    - type: recall_at_3
      value: 68.062
    - type: recall_at_5
      value: 73.40299999999999
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 72.876
    - type: ap
      value: 67.15477852410164
    - type: f1
      value: 72.65147370025373
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: mteb/msmarco
      config: default
      split: dev
      revision: c5a29a104738b98a9e76336939199e264163d4a0
    metrics:
    - type: map_at_1
      value: 21.748
    - type: map_at_10
      value: 34.626000000000005
    - type: map_at_100
      value: 35.813
    - type: map_at_1000
      value: 35.859
    - type: map_at_3
      value: 30.753000000000004
    - type: map_at_5
      value: 33.049
    - type: mrr_at_1
      value: 22.35
    - type: mrr_at_10
      value: 35.23
    - type: mrr_at_100
      value: 36.359
    - type: mrr_at_1000
      value: 36.399
    - type: mrr_at_3
      value: 31.436999999999998
    - type: mrr_at_5
      value: 33.687
    - type: ndcg_at_1
      value: 22.364
    - type: ndcg_at_10
      value: 41.677
    - type: ndcg_at_100
      value: 47.355999999999995
    - type: ndcg_at_1000
      value: 48.494
    - type: ndcg_at_3
      value: 33.85
    - type: ndcg_at_5
      value: 37.942
    - type: precision_at_1
      value: 22.364
    - type: precision_at_10
      value: 6.6000000000000005
    - type: precision_at_100
      value: 0.9450000000000001
    - type: precision_at_1000
      value: 0.104
    - type: precision_at_3
      value: 14.527000000000001
    - type: precision_at_5
      value: 10.796999999999999
    - type: recall_at_1
      value: 21.748
    - type: recall_at_10
      value: 63.292
    - type: recall_at_100
      value: 89.427
    - type: recall_at_1000
      value: 98.13499999999999
    - type: recall_at_3
      value: 42.126000000000005
    - type: recall_at_5
      value: 51.968
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 92.62425900592795
    - type: f1
      value: 92.08497761553683
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 64.51436388508893
    - type: f1
      value: 45.884016531912906
  - task:
      type: Classification
    dataset:
      name: MTEB MasakhaNEWSClassification (eng)
      type: masakhane/masakhanews
      config: eng
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: accuracy
      value: 76.57172995780591
    - type: f1
      value: 75.52979910878491
  - task:
      type: Clustering
    dataset:
      name: MTEB MasakhaNEWSClusteringP2P (eng)
      type: masakhane/masakhanews
      config: eng
      split: test
      revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
    metrics:
    - type: v_measure
      value: 44.84052695201612
    - type: v_measure
      value: 21.443971229936494
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
    metrics:
    - type: accuracy
      value: 65.79354404841965
    - type: f1
      value: 63.17260074126185
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: 7d571f92784cd94a019292a1f45445077d0ef634
    metrics:
    - type: accuracy
      value: 71.09616677874916
    - type: f1
      value: 69.74285784421075
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: v_measure
      value: 31.474709231086184
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: v_measure
      value: 28.93630367824217
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking
      type: mteb/mind_small
      config: default
      split: test
      revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69
    metrics:
    - type: map
      value: 29.08234393834005
    - type: mrr
      value: 29.740466971605432
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: mteb/nfcorpus
      config: default
      split: test
      revision: ec0fa4fe99da2ff19ca1214b7966684033a58814
    metrics:
    - type: map_at_1
      value: 6.2059999999999995
    - type: map_at_10
      value: 14.442
    - type: map_at_100
      value: 18.005
    - type: map_at_1000
      value: 19.488
    - type: map_at_3
      value: 10.666
    - type: map_at_5
      value: 12.45
    - type: mrr_at_1
      value: 47.678
    - type: mrr_at_10
      value: 57.519
    - type: mrr_at_100
      value: 58.13700000000001
    - type: mrr_at_1000
      value: 58.167
    - type: mrr_at_3
      value: 55.779
    - type: mrr_at_5
      value: 56.940000000000005
    - type: ndcg_at_1
      value: 45.82
    - type: ndcg_at_10
      value: 37.651
    - type: ndcg_at_100
      value: 34.001999999999995
    - type: ndcg_at_1000
      value: 42.626
    - type: ndcg_at_3
      value: 43.961
    - type: ndcg_at_5
      value: 41.461
    - type: precision_at_1
      value: 47.678
    - type: precision_at_10
      value: 27.584999999999997
    - type: precision_at_100
      value: 8.455
    - type: precision_at_1000
      value: 2.118
    - type: precision_at_3
      value: 41.692
    - type: precision_at_5
      value: 36.161
    - type: recall_at_1
      value: 6.2059999999999995
    - type: recall_at_10
      value: 18.599
    - type: recall_at_100
      value: 33.608
    - type: recall_at_1000
      value: 65.429
    - type: recall_at_3
      value: 12.126000000000001
    - type: recall_at_5
      value: 14.902000000000001
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: mteb/nq
      config: default
      split: test
      revision: b774495ed302d8c44a3a7ea25c90dbce03968f31
    metrics:
    - type: map_at_1
      value: 39.117000000000004
    - type: map_at_10
      value: 55.535000000000004
    - type: map_at_100
      value: 56.32899999999999
    - type: map_at_1000
      value: 56.34400000000001
    - type: map_at_3
      value: 51.439
    - type: map_at_5
      value: 53.89699999999999
    - type: mrr_at_1
      value: 43.714
    - type: mrr_at_10
      value: 58.05200000000001
    - type: mrr_at_100
      value: 58.582
    - type: mrr_at_1000
      value: 58.592
    - type: mrr_at_3
      value: 54.896
    - type: mrr_at_5
      value: 56.874
    - type: ndcg_at_1
      value: 43.685
    - type: ndcg_at_10
      value: 63.108
    - type: ndcg_at_100
      value: 66.231
    - type: ndcg_at_1000
      value: 66.583
    - type: ndcg_at_3
      value: 55.659000000000006
    - type: ndcg_at_5
      value: 59.681
    - type: precision_at_1
      value: 43.685
    - type: precision_at_10
      value: 9.962
    - type: precision_at_100
      value: 1.174
    - type: precision_at_1000
      value: 0.121
    - type: precision_at_3
      value: 24.961
    - type: precision_at_5
      value: 17.352
    - type: recall_at_1
      value: 39.117000000000004
    - type: recall_at_10
      value: 83.408
    - type: recall_at_100
      value: 96.553
    - type: recall_at_1000
      value: 99.136
    - type: recall_at_3
      value: 64.364
    - type: recall_at_5
      value: 73.573
  - task:
      type: Classification
    dataset:
      name: MTEB NewsClassification
      type: ag_news
      config: default
      split: test
      revision: eb185aade064a813bc0b7f42de02595523103ca4
    metrics:
    - type: accuracy
      value: 78.87763157894737
    - type: f1
      value: 78.69611753876177
  - 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: 62
    - type: cos_sim_ap
      value: 62.26837791655737
    - type: cos_sim_f1
      value: 62.607449856733524
    - type: cos_sim_precision
      value: 46.36604774535809
    - type: cos_sim_recall
      value: 96.36163175303197
    - type: dot_accuracy
      value: 62
    - type: dot_ap
      value: 62.26736459439965
    - type: dot_f1
      value: 62.607449856733524
    - type: dot_precision
      value: 46.36604774535809
    - type: dot_recall
      value: 96.36163175303197
    - type: euclidean_accuracy
      value: 62
    - type: euclidean_ap
      value: 62.26826112548132
    - type: euclidean_f1
      value: 62.607449856733524
    - type: euclidean_precision
      value: 46.36604774535809
    - type: euclidean_recall
      value: 96.36163175303197
    - type: manhattan_accuracy
      value: 62
    - type: manhattan_ap
      value: 62.26223761507973
    - type: manhattan_f1
      value: 62.585034013605444
    - type: manhattan_precision
      value: 46.34146341463415
    - type: manhattan_recall
      value: 96.36163175303197
    - type: max_accuracy
      value: 62
    - type: max_ap
      value: 62.26837791655737
    - type: max_f1
      value: 62.607449856733524
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: mteb/quora
      config: default
      split: test
      revision: e4e08e0b7dbe3c8700f0daef558ff32256715259
    metrics:
    - type: map_at_1
      value: 69.90899999999999
    - type: map_at_10
      value: 83.56700000000001
    - type: map_at_100
      value: 84.19200000000001
    - type: map_at_1000
      value: 84.212
    - type: map_at_3
      value: 80.658
    - type: map_at_5
      value: 82.473
    - type: mrr_at_1
      value: 80.4
    - type: mrr_at_10
      value: 86.699
    - type: mrr_at_100
      value: 86.798
    - type: mrr_at_1000
      value: 86.80099999999999
    - type: mrr_at_3
      value: 85.677
    - type: mrr_at_5
      value: 86.354
    - type: ndcg_at_1
      value: 80.43
    - type: ndcg_at_10
      value: 87.41
    - type: ndcg_at_100
      value: 88.653
    - type: ndcg_at_1000
      value: 88.81599999999999
    - type: ndcg_at_3
      value: 84.516
    - type: ndcg_at_5
      value: 86.068
    - type: precision_at_1
      value: 80.43
    - type: precision_at_10
      value: 13.234000000000002
    - type: precision_at_100
      value: 1.513
    - type: precision_at_1000
      value: 0.156
    - type: precision_at_3
      value: 36.93
    - type: precision_at_5
      value: 24.26
    - type: recall_at_1
      value: 69.90899999999999
    - type: recall_at_10
      value: 94.687
    - type: recall_at_100
      value: 98.96000000000001
    - type: recall_at_1000
      value: 99.79599999999999
    - type: recall_at_3
      value: 86.25699999999999
    - type: recall_at_5
      value: 90.70700000000001
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: v_measure
      value: 46.02256865360266
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
    metrics:
    - type: v_measure
      value: 62.43157528757563
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: mteb/scidocs
      config: default
      split: test
      revision: f8c2fcf00f625baaa80f62ec5bd9e1fff3b8ae88
    metrics:
    - type: map_at_1
      value: 5.093
    - type: map_at_10
      value: 12.982
    - type: map_at_100
      value: 15.031
    - type: map_at_1000
      value: 15.334
    - type: map_at_3
      value: 9.339
    - type: map_at_5
      value: 11.183
    - type: mrr_at_1
      value: 25.1
    - type: mrr_at_10
      value: 36.257
    - type: mrr_at_100
      value: 37.351
    - type: mrr_at_1000
      value: 37.409
    - type: mrr_at_3
      value: 33.050000000000004
    - type: mrr_at_5
      value: 35.205
    - type: ndcg_at_1
      value: 25.1
    - type: ndcg_at_10
      value: 21.361
    - type: ndcg_at_100
      value: 29.396
    - type: ndcg_at_1000
      value: 34.849999999999994
    - type: ndcg_at_3
      value: 20.704
    - type: ndcg_at_5
      value: 18.086
    - type: precision_at_1
      value: 25.1
    - type: precision_at_10
      value: 10.94
    - type: precision_at_100
      value: 2.257
    - type: precision_at_1000
      value: 0.358
    - type: precision_at_3
      value: 19.467000000000002
    - type: precision_at_5
      value: 15.98
    - type: recall_at_1
      value: 5.093
    - type: recall_at_10
      value: 22.177
    - type: recall_at_100
      value: 45.842
    - type: recall_at_1000
      value: 72.598
    - type: recall_at_3
      value: 11.833
    - type: recall_at_5
      value: 16.173000000000002
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cos_sim_pearson
      value: 73.56535226754596
    - type: cos_sim_spearman
      value: 69.32425977603488
    - type: euclidean_pearson
      value: 71.32425703470898
    - type: euclidean_spearman
      value: 69.32425217267013
    - type: manhattan_pearson
      value: 71.25897281394246
    - type: manhattan_spearman
      value: 69.27132577049578
  - task:
      type: STS
    dataset:
      name: MTEB STS12
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cos_sim_pearson
      value: 69.66387868726018
    - type: cos_sim_spearman
      value: 67.85470749045027
    - type: euclidean_pearson
      value: 66.62075098063795
    - type: euclidean_spearman
      value: 67.85470749045027
    - type: manhattan_pearson
      value: 66.61455061901262
    - type: manhattan_spearman
      value: 67.87229618498695
  - task:
      type: STS
    dataset:
      name: MTEB STS13
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cos_sim_pearson
      value: 75.65731331392575
    - type: cos_sim_spearman
      value: 77.48991626780108
    - type: euclidean_pearson
      value: 77.19884738623692
    - type: euclidean_spearman
      value: 77.48985836619045
    - type: manhattan_pearson
      value: 77.0656684243772
    - type: manhattan_spearman
      value: 77.30289226582691
  - task:
      type: STS
    dataset:
      name: MTEB STS14
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cos_sim_pearson
      value: 69.37003253666457
    - type: cos_sim_spearman
      value: 69.77157648098141
    - type: euclidean_pearson
      value: 69.39543876030432
    - type: euclidean_spearman
      value: 69.77157648098141
    - type: manhattan_pearson
      value: 69.29901600459745
    - type: manhattan_spearman
      value: 69.65074167527128
  - task:
      type: STS
    dataset:
      name: MTEB STS15
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cos_sim_pearson
      value: 78.56777256540136
    - type: cos_sim_spearman
      value: 80.16458787843023
    - type: euclidean_pearson
      value: 80.16475730686916
    - type: euclidean_spearman
      value: 80.16458787843023
    - type: manhattan_pearson
      value: 80.12814463670401
    - type: manhattan_spearman
      value: 80.1357907984809
  - task:
      type: STS
    dataset:
      name: MTEB STS16
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cos_sim_pearson
      value: 76.09572350919031
    - type: cos_sim_spearman
      value: 77.94490233429326
    - type: euclidean_pearson
      value: 78.36595251203524
    - type: euclidean_spearman
      value: 77.94490233429326
    - type: manhattan_pearson
      value: 78.41538768125166
    - type: manhattan_spearman
      value: 78.01244379569542
  - 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: 80.7843552187951
    - type: cos_sim_spearman
      value: 82.28085055047386
    - type: euclidean_pearson
      value: 82.37373672515267
    - type: euclidean_spearman
      value: 82.28085055047386
    - type: manhattan_pearson
      value: 82.39387241346917
    - type: manhattan_spearman
      value: 82.36503339515906
  - 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: 68.29963929962095
    - type: cos_sim_spearman
      value: 67.96868942546051
    - type: euclidean_pearson
      value: 68.93524903869285
    - type: euclidean_spearman
      value: 67.96868942546051
    - type: manhattan_pearson
      value: 68.79144468444811
    - type: manhattan_spearman
      value: 67.69311483884324
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cos_sim_pearson
      value: 72.84789696700685
    - type: cos_sim_spearman
      value: 75.67875747588545
    - type: euclidean_pearson
      value: 75.07752300463038
    - type: euclidean_spearman
      value: 75.67875747588545
    - type: manhattan_pearson
      value: 74.97934248140928
    - type: manhattan_spearman
      value: 75.62525644178724
  - 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: 72.84789702519309
    - type: cos_sim_spearman
      value: 75.67875747588545
    - type: euclidean_pearson
      value: 75.07752310061133
    - type: euclidean_spearman
      value: 75.67875747588545
    - type: manhattan_pearson
      value: 74.97934257159595
    - type: manhattan_spearman
      value: 75.62525644178724
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: map
      value: 81.55557720431086
    - type: mrr
      value: 94.91178665198272
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: mteb/scifact
      config: default
      split: test
      revision: 0228b52cf27578f30900b9e5271d331663a030d7
    metrics:
    - type: map_at_1
      value: 59.260999999999996
    - type: map_at_10
      value: 69.36099999999999
    - type: map_at_100
      value: 69.868
    - type: map_at_1000
      value: 69.877
    - type: map_at_3
      value: 66.617
    - type: map_at_5
      value: 68.061
    - type: mrr_at_1
      value: 62.333000000000006
    - type: mrr_at_10
      value: 70.533
    - type: mrr_at_100
      value: 70.966
    - type: mrr_at_1000
      value: 70.975
    - type: mrr_at_3
      value: 68.667
    - type: mrr_at_5
      value: 69.717
    - type: ndcg_at_1
      value: 62.333000000000006
    - type: ndcg_at_10
      value: 73.82300000000001
    - type: ndcg_at_100
      value: 76.122
    - type: ndcg_at_1000
      value: 76.374
    - type: ndcg_at_3
      value: 69.27499999999999
    - type: ndcg_at_5
      value: 71.33
    - type: precision_at_1
      value: 62.333000000000006
    - type: precision_at_10
      value: 9.8
    - type: precision_at_100
      value: 1.097
    - type: precision_at_1000
      value: 0.11199999999999999
    - type: precision_at_3
      value: 26.889000000000003
    - type: precision_at_5
      value: 17.599999999999998
    - type: recall_at_1
      value: 59.260999999999996
    - type: recall_at_10
      value: 86.2
    - type: recall_at_100
      value: 96.667
    - type: recall_at_1000
      value: 98.667
    - type: recall_at_3
      value: 74.006
    - type: recall_at_5
      value: 79.167
  - 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: 95.20169041096409
    - type: cos_sim_f1
      value: 90.76224129227664
    - type: cos_sim_precision
      value: 91.64118246687055
    - type: cos_sim_recall
      value: 89.9
    - type: dot_accuracy
      value: 99.81881188118813
    - type: dot_ap
      value: 95.20169041096409
    - type: dot_f1
      value: 90.76224129227664
    - type: dot_precision
      value: 91.64118246687055
    - type: dot_recall
      value: 89.9
    - type: euclidean_accuracy
      value: 99.81881188118813
    - type: euclidean_ap
      value: 95.2016904109641
    - type: euclidean_f1
      value: 90.76224129227664
    - type: euclidean_precision
      value: 91.64118246687055
    - type: euclidean_recall
      value: 89.9
    - type: manhattan_accuracy
      value: 99.81881188118813
    - type: manhattan_ap
      value: 95.22680188132777
    - type: manhattan_f1
      value: 90.79013588324108
    - type: manhattan_precision
      value: 91.38804457953394
    - type: manhattan_recall
      value: 90.2
    - type: max_accuracy
      value: 99.81881188118813
    - type: max_ap
      value: 95.22680188132777
    - type: max_f1
      value: 90.79013588324108
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: v_measure
      value: 57.8638628701308
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: v_measure
      value: 37.82028248106046
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: map
      value: 50.870860210170946
    - type: mrr
      value: 51.608084521687466
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cos_sim_pearson
      value: 31.60384207444685
    - type: cos_sim_spearman
      value: 30.84047452209471
    - type: dot_pearson
      value: 31.60384104417333
    - type: dot_spearman
      value: 30.84047452209471
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: mteb/trec-covid
      config: default
      split: test
      revision: bb9466bac8153a0349341eb1b22e06409e78ef4e
    metrics:
    - type: map_at_1
      value: 0.246
    - type: map_at_10
      value: 2.051
    - type: map_at_100
      value: 13.129
    - type: map_at_1000
      value: 31.56
    - type: map_at_3
      value: 0.681
    - type: map_at_5
      value: 1.105
    - 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: 87
    - type: ndcg_at_10
      value: 80.716
    - type: ndcg_at_100
      value: 63.83
    - type: ndcg_at_1000
      value: 56.215
    - type: ndcg_at_3
      value: 84.531
    - type: ndcg_at_5
      value: 84.777
    - type: precision_at_1
      value: 94
    - type: precision_at_10
      value: 84.6
    - type: precision_at_100
      value: 66.03999999999999
    - type: precision_at_1000
      value: 24.878
    - type: precision_at_3
      value: 88.667
    - type: precision_at_5
      value: 89.60000000000001
    - type: recall_at_1
      value: 0.246
    - type: recall_at_10
      value: 2.2079999999999997
    - type: recall_at_100
      value: 15.895999999999999
    - type: recall_at_1000
      value: 52.683
    - type: recall_at_3
      value: 0.7040000000000001
    - type: recall_at_5
      value: 1.163
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: mteb/touche2020
      config: default
      split: test
      revision: a34f9a33db75fa0cbb21bb5cfc3dae8dc8bec93f
    metrics:
    - type: map_at_1
      value: 3.852
    - type: map_at_10
      value: 14.316
    - type: map_at_100
      value: 20.982
    - type: map_at_1000
      value: 22.58
    - type: map_at_3
      value: 7.767
    - type: map_at_5
      value: 10.321
    - type: mrr_at_1
      value: 51.019999999999996
    - type: mrr_at_10
      value: 66.365
    - type: mrr_at_100
      value: 66.522
    - type: mrr_at_1000
      value: 66.522
    - type: mrr_at_3
      value: 62.925
    - type: mrr_at_5
      value: 64.762
    - type: ndcg_at_1
      value: 46.939
    - type: ndcg_at_10
      value: 34.516999999999996
    - type: ndcg_at_100
      value: 44.25
    - type: ndcg_at_1000
      value: 54.899
    - type: ndcg_at_3
      value: 40.203
    - type: ndcg_at_5
      value: 37.004
    - type: precision_at_1
      value: 51.019999999999996
    - type: precision_at_10
      value: 29.796
    - type: precision_at_100
      value: 8.633000000000001
    - type: precision_at_1000
      value: 1.584
    - type: precision_at_3
      value: 40.816
    - type: precision_at_5
      value: 35.918
    - type: recall_at_1
      value: 3.852
    - type: recall_at_10
      value: 20.891000000000002
    - type: recall_at_100
      value: 52.428
    - type: recall_at_1000
      value: 84.34899999999999
    - type: recall_at_3
      value: 8.834
    - type: recall_at_5
      value: 12.909
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 64.7092
    - type: ap
      value: 11.972915012305819
    - type: f1
      value: 49.91050149892115
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 56.737408036219584
    - type: f1
      value: 57.07235266246011
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: v_measure
      value: 35.9147539025798
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cos_sim_accuracy
      value: 82.52369315133814
    - type: cos_sim_ap
      value: 62.34858091376534
    - type: cos_sim_f1
      value: 58.18225190839694
    - type: cos_sim_precision
      value: 53.09098824553766
    - type: cos_sim_recall
      value: 64.35356200527704
    - type: dot_accuracy
      value: 82.52369315133814
    - type: dot_ap
      value: 62.34857753814992
    - type: dot_f1
      value: 58.18225190839694
    - type: dot_precision
      value: 53.09098824553766
    - type: dot_recall
      value: 64.35356200527704
    - type: euclidean_accuracy
      value: 82.52369315133814
    - type: euclidean_ap
      value: 62.34857756663386
    - type: euclidean_f1
      value: 58.18225190839694
    - type: euclidean_precision
      value: 53.09098824553766
    - type: euclidean_recall
      value: 64.35356200527704
    - type: manhattan_accuracy
      value: 82.49389044525243
    - type: manhattan_ap
      value: 62.32245347238179
    - type: manhattan_f1
      value: 58.206309819213054
    - type: manhattan_precision
      value: 52.70704044511021
    - type: manhattan_recall
      value: 64.9868073878628
    - type: max_accuracy
      value: 82.52369315133814
    - type: max_ap
      value: 62.34858091376534
    - type: max_f1
      value: 58.206309819213054
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cos_sim_accuracy
      value: 88.34555827220863
    - type: cos_sim_ap
      value: 84.84152481680071
    - type: cos_sim_f1
      value: 76.860456739428
    - type: cos_sim_precision
      value: 72.21470150263978
    - type: cos_sim_recall
      value: 82.14505697566985
    - type: dot_accuracy
      value: 88.34555827220863
    - type: dot_ap
      value: 84.84152743322608
    - type: dot_f1
      value: 76.860456739428
    - type: dot_precision
      value: 72.21470150263978
    - type: dot_recall
      value: 82.14505697566985
    - type: euclidean_accuracy
      value: 88.34555827220863
    - type: euclidean_ap
      value: 84.84152589453169
    - type: euclidean_f1
      value: 76.860456739428
    - type: euclidean_precision
      value: 72.21470150263978
    - type: euclidean_recall
      value: 82.14505697566985
    - type: manhattan_accuracy
      value: 88.38242713548337
    - type: manhattan_ap
      value: 84.8112124970968
    - type: manhattan_f1
      value: 76.83599206057487
    - type: manhattan_precision
      value: 73.51244900829934
    - type: manhattan_recall
      value: 80.47428395441946
    - type: max_accuracy
      value: 88.38242713548337
    - type: max_ap
      value: 84.84152743322608
    - type: max_f1
      value: 76.860456739428
  - task:
      type: Clustering
    dataset:
      name: MTEB WikiCitiesClustering
      type: jinaai/cities_wiki_clustering
      config: default
      split: test
      revision: ddc9ee9242fa65332597f70e967ecc38b9d734fa
    metrics:
    - type: v_measure
      value: 85.5314389263015
---

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

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