---
base_model: Snowflake/snowflake-arctic-embed-m-v1.5
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-m-v1.5
  results:
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      type: Retrieval
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      type: mteb/arguana
      config: default
      split: test
      revision: c22ab2a51041ffd869aaddef7af8d8215647e41a
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  - task:
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  - task:
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    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: mteb/cqadupstack-physics
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  - task:
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      type: mteb/cqadupstack
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      revision: CQADupstackRetrieval is a combined dataset
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  - task:
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  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: mteb/cqadupstack-unix
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  - task:
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    dataset:
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      type: mteb/cqadupstack-wordpress
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      revision: 4ffe81d471b1924886b33c7567bfb200e9eec5c4
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  - task:
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  - task:
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  - task:
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  - task:
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      type: mteb/amazon_counterfactual
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  - task:
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  - task:
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  - task:
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  - task:
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    dataset:
      name: MTEB ArxivClusteringS2S (default)
      type: mteb/arxiv-clustering-s2s
      config: default
      split: test
      revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53
    metrics:
    - type: main_score
      value: 34.12071448053325
    - type: v_measure
      value: 34.12071448053325
    - type: v_measure_std
      value: 13.7019879046405
  - task:
      type: Reranking
    dataset:
      name: MTEB AskUbuntuDupQuestions (default)
      type: mteb/askubuntudupquestions-reranking
      config: default
      split: test
      revision: 2000358ca161889fa9c082cb41daa8dcfb161a54
    metrics:
    - type: main_score
      value: 61.597667288657846
    - type: map
      value: 61.597667288657846
    - type: mrr
      value: 75.57940904893813
    - type: nAUC_map_diff1
      value: 8.745172077340095
    - type: nAUC_map_max
      value: 20.114863024035493
    - type: nAUC_map_std
      value: 15.991351189572192
    - type: nAUC_mrr_diff1
      value: 20.781369244159983
    - type: nAUC_mrr_max
      value: 30.78542570228559
    - type: nAUC_mrr_std
      value: 19.861484857303676
  - task:
      type: STS
    dataset:
      name: MTEB BIOSSES (default)
      type: mteb/biosses-sts
      config: default
      split: test
      revision: d3fb88f8f02e40887cd149695127462bbcf29b4a
    metrics:
    - type: cosine_pearson
      value: 88.55587996301419
    - type: cosine_spearman
      value: 86.40317357420093
    - type: euclidean_pearson
      value: 86.93771958250231
    - type: euclidean_spearman
      value: 86.40317357420093
    - type: main_score
      value: 86.40317357420093
    - type: manhattan_pearson
      value: 86.92196577117366
    - type: manhattan_spearman
      value: 85.79834051556095
    - type: pearson
      value: 88.55587996301419
    - type: spearman
      value: 86.40317357420093
  - task:
      type: Classification
    dataset:
      name: MTEB Banking77Classification (default)
      type: mteb/banking77
      config: default
      split: test
      revision: 0fd18e25b25c072e09e0d92ab615fda904d66300
    metrics:
    - type: accuracy
      value: 80.0064935064935
    - type: f1
      value: 79.29524254086299
    - type: f1_weighted
      value: 79.295242540863
    - type: main_score
      value: 80.0064935064935
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringP2P (default)
      type: mteb/biorxiv-clustering-p2p
      config: default
      split: test
      revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40
    metrics:
    - type: main_score
      value: 35.27186813341181
    - type: v_measure
      value: 35.27186813341181
    - type: v_measure_std
      value: 0.8621482145872432
  - task:
      type: Clustering
    dataset:
      name: MTEB BiorxivClusteringS2S (default)
      type: mteb/biorxiv-clustering-s2s
      config: default
      split: test
      revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908
    metrics:
    - type: main_score
      value: 28.411805064852295
    - type: v_measure
      value: 28.411805064852295
    - type: v_measure_std
      value: 0.7194290078011281
  - task:
      type: Classification
    dataset:
      name: MTEB EmotionClassification (default)
      type: mteb/emotion
      config: default
      split: test
      revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37
    metrics:
    - type: accuracy
      value: 43.675
    - type: f1
      value: 40.15061931375577
    - type: f1_weighted
      value: 45.714186572727066
    - type: main_score
      value: 43.675
  - task:
      type: Classification
    dataset:
      name: MTEB ImdbClassification (default)
      type: mteb/imdb
      config: default
      split: test
      revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7
    metrics:
    - type: accuracy
      value: 84.35640000000001
    - type: ap
      value: 79.07507736685174
    - type: ap_weighted
      value: 79.07507736685174
    - type: f1
      value: 84.32288494833531
    - type: f1_weighted
      value: 84.32288494833531
    - type: main_score
      value: 84.35640000000001
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPDomainClassification (en)
      type: mteb/mtop_domain
      config: en
      split: test
      revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
    metrics:
    - type: accuracy
      value: 91.35658914728684
    - type: f1
      value: 90.86877537911086
    - type: f1_weighted
      value: 91.3282092774443
    - type: main_score
      value: 91.35658914728684
  - task:
      type: Classification
    dataset:
      name: MTEB MTOPIntentClassification (en)
      type: mteb/mtop_intent
      config: en
      split: test
      revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
    metrics:
    - type: accuracy
      value: 60.63611491108071
    - type: f1
      value: 42.78886482112741
    - type: f1_weighted
      value: 63.44208631840539
    - type: main_score
      value: 60.63611491108071
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveIntentClassification (en)
      type: mteb/amazon_massive_intent
      config: en
      split: test
      revision: 4672e20407010da34463acc759c162ca9734bca6
    metrics:
    - type: accuracy
      value: 66.68796234028245
    - type: f1
      value: 64.44940791000278
    - type: f1_weighted
      value: 65.77554417406792
    - type: main_score
      value: 66.68796234028245
  - task:
      type: Classification
    dataset:
      name: MTEB MassiveScenarioClassification (en)
      type: mteb/amazon_massive_scenario
      config: en
      split: test
      revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
    metrics:
    - type: accuracy
      value: 73.0598520511096
    - type: f1
      value: 72.14267273884774
    - type: f1_weighted
      value: 72.93345180137516
    - type: main_score
      value: 73.0598520511096
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringP2P (default)
      type: mteb/medrxiv-clustering-p2p
      config: default
      split: test
      revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73
    metrics:
    - type: main_score
      value: 31.143081341699606
    - type: v_measure
      value: 31.143081341699606
    - type: v_measure_std
      value: 1.5578716347076906
  - task:
      type: Clustering
    dataset:
      name: MTEB MedrxivClusteringS2S (default)
      type: mteb/medrxiv-clustering-s2s
      config: default
      split: test
      revision: 35191c8c0dca72d8ff3efcd72aa802307d469663
    metrics:
    - type: main_score
      value: 27.010818869829556
    - type: v_measure
      value: 27.010818869829556
    - type: v_measure_std
      value: 1.1771554540819378
  - task:
      type: Reranking
    dataset:
      name: MTEB MindSmallReranking (default)
      type: mteb/mind_small
      config: default
      split: test
      revision: 59042f120c80e8afa9cdbb224f67076cec0fc9a7
    metrics:
    - type: main_score
      value: 30.20503776754942
    - type: map
      value: 30.20503776754942
    - type: mrr
      value: 31.076636002733437
    - type: nAUC_map_diff1
      value: 7.290568655287842
    - type: nAUC_map_max
      value: -21.381599355932945
    - type: nAUC_map_std
      value: -7.709920607543168
    - type: nAUC_mrr_diff1
      value: 7.558397329284913
    - type: nAUC_mrr_max
      value: -15.981397186427607
    - type: nAUC_mrr_std
      value: -4.870495243168834
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClustering (default)
      type: mteb/reddit-clustering
      config: default
      split: test
      revision: 24640382cdbf8abc73003fb0fa6d111a705499eb
    metrics:
    - type: main_score
      value: 51.85893476633338
    - type: v_measure
      value: 51.85893476633338
    - type: v_measure_std
      value: 4.704770139385852
  - task:
      type: Clustering
    dataset:
      name: MTEB RedditClusteringP2P (default)
      type: mteb/reddit-clustering-p2p
      config: default
      split: test
      revision: 385e3cb46b4cfa89021f56c4380204149d0efe33
    metrics:
    - type: main_score
      value: 61.8124222918822
    - type: v_measure
      value: 61.8124222918822
    - type: v_measure_std
      value: 11.994472578100165
  - task:
      type: STS
    dataset:
      name: MTEB SICK-R (default)
      type: mteb/sickr-sts
      config: default
      split: test
      revision: 20a6d6f312dd54037fe07a32d58e5e168867909d
    metrics:
    - type: cosine_pearson
      value: 77.63310776935984
    - type: cosine_spearman
      value: 69.86468291111039
    - type: euclidean_pearson
      value: 73.91537077798837
    - type: euclidean_spearman
      value: 69.86468376650203
    - type: main_score
      value: 69.86468291111039
    - type: manhattan_pearson
      value: 73.68616048370464
    - type: manhattan_spearman
      value: 69.76232036206659
    - type: pearson
      value: 77.63310776935984
    - type: spearman
      value: 69.86468291111039
  - task:
      type: STS
    dataset:
      name: MTEB STS12 (default)
      type: mteb/sts12-sts
      config: default
      split: test
      revision: a0d554a64d88156834ff5ae9920b964011b16384
    metrics:
    - type: cosine_pearson
      value: 57.71716838245049
    - type: cosine_spearman
      value: 61.797855543446424
    - type: euclidean_pearson
      value: 58.22958675325848
    - type: euclidean_spearman
      value: 61.797855543446424
    - type: main_score
      value: 61.797855543446424
    - type: manhattan_pearson
      value: 57.63117544997929
    - type: manhattan_spearman
      value: 61.3629404350085
    - type: pearson
      value: 57.71716838245049
    - type: spearman
      value: 61.797855543446424
  - task:
      type: STS
    dataset:
      name: MTEB STS13 (default)
      type: mteb/sts13-sts
      config: default
      split: test
      revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca
    metrics:
    - type: cosine_pearson
      value: 82.30260026790903
    - type: cosine_spearman
      value: 82.66959813070869
    - type: euclidean_pearson
      value: 82.08383017580783
    - type: euclidean_spearman
      value: 82.66959813070869
    - type: main_score
      value: 82.66959813070869
    - type: manhattan_pearson
      value: 81.77991451392153
    - type: manhattan_spearman
      value: 82.3652534745606
    - type: pearson
      value: 82.30260026790903
    - type: spearman
      value: 82.66959813070869
  - task:
      type: STS
    dataset:
      name: MTEB STS14 (default)
      type: mteb/sts14-sts
      config: default
      split: test
      revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375
    metrics:
    - type: cosine_pearson
      value: 71.50608384084478
    - type: cosine_spearman
      value: 68.94968064977785
    - type: euclidean_pearson
      value: 70.73381299949564
    - type: euclidean_spearman
      value: 68.94968064977785
    - type: main_score
      value: 68.94968064977785
    - type: manhattan_pearson
      value: 70.5385486953787
    - type: manhattan_spearman
      value: 68.82132770672365
    - type: pearson
      value: 71.50608384084478
    - type: spearman
      value: 68.94968064977785
  - task:
      type: STS
    dataset:
      name: MTEB STS15 (default)
      type: mteb/sts15-sts
      config: default
      split: test
      revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3
    metrics:
    - type: cosine_pearson
      value: 73.66969825874907
    - type: cosine_spearman
      value: 75.55374982088381
    - type: euclidean_pearson
      value: 75.9339313749594
    - type: euclidean_spearman
      value: 75.55374982088381
    - type: main_score
      value: 75.55374982088381
    - type: manhattan_pearson
      value: 75.88287553383817
    - type: manhattan_spearman
      value: 75.50729812977688
    - type: pearson
      value: 73.66969825874907
    - type: spearman
      value: 75.55374982088381
  - task:
      type: STS
    dataset:
      name: MTEB STS16 (default)
      type: mteb/sts16-sts
      config: default
      split: test
      revision: 4d8694f8f0e0100860b497b999b3dbed754a0513
    metrics:
    - type: cosine_pearson
      value: 74.5954724414016
    - type: cosine_spearman
      value: 77.2688820850505
    - type: euclidean_pearson
      value: 77.19866353971555
    - type: euclidean_spearman
      value: 77.2688820850505
    - type: main_score
      value: 77.2688820850505
    - type: manhattan_pearson
      value: 77.27072603680978
    - type: manhattan_spearman
      value: 77.29408453673607
    - type: pearson
      value: 74.5954724414016
    - type: spearman
      value: 77.2688820850505
  - task:
      type: STS
    dataset:
      name: MTEB STS17 (en-en)
      type: mteb/sts17-crosslingual-sts
      config: en-en
      split: test
      revision: faeb762787bd10488a50c8b5be4a3b82e411949c
    metrics:
    - type: cosine_pearson
      value: 71.52588722654055
    - type: cosine_spearman
      value: 74.97235736456061
    - type: euclidean_pearson
      value: 74.51952528854038
    - type: euclidean_spearman
      value: 74.97235736456061
    - type: main_score
      value: 74.97235736456061
    - type: manhattan_pearson
      value: 74.48272300884209
    - type: manhattan_spearman
      value: 74.80633649415176
    - type: pearson
      value: 71.52588722654055
    - type: spearman
      value: 74.97235736456061
  - task:
      type: STS
    dataset:
      name: MTEB STS22 (en)
      type: mteb/sts22-crosslingual-sts
      config: en
      split: test
      revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
    metrics:
    - type: cosine_pearson
      value: 68.80031120401976
    - type: cosine_spearman
      value: 69.07945196478491
    - type: euclidean_pearson
      value: 68.99674496430792
    - type: euclidean_spearman
      value: 69.07945196478491
    - type: main_score
      value: 69.07945196478491
    - type: manhattan_pearson
      value: 69.00236107775687
    - type: manhattan_spearman
      value: 68.98064879049272
    - type: pearson
      value: 68.80031120401976
    - type: spearman
      value: 69.07945196478491
  - task:
      type: STS
    dataset:
      name: MTEB STSBenchmark (default)
      type: mteb/stsbenchmark-sts
      config: default
      split: test
      revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831
    metrics:
    - type: cosine_pearson
      value: 65.6898007230089
    - type: cosine_spearman
      value: 69.72386211803668
    - type: euclidean_pearson
      value: 69.04523003701475
    - type: euclidean_spearman
      value: 69.72386211803668
    - type: main_score
      value: 69.72386211803668
    - type: manhattan_pearson
      value: 68.80479743770702
    - type: manhattan_spearman
      value: 69.43264575177459
    - type: pearson
      value: 65.6898007230089
    - type: spearman
      value: 69.72386211803668
  - task:
      type: Reranking
    dataset:
      name: MTEB SciDocsRR (default)
      type: mteb/scidocs-reranking
      config: default
      split: test
      revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab
    metrics:
    - type: main_score
      value: 79.74088066874383
    - type: map
      value: 79.74088066874383
    - type: mrr
      value: 94.47697455050397
    - type: nAUC_map_diff1
      value: 8.036086256905502
    - type: nAUC_map_max
      value: 54.88199803816819
    - type: nAUC_map_std
      value: 69.16267942176574
    - type: nAUC_mrr_diff1
      value: 50.020738477678115
    - type: nAUC_mrr_max
      value: 83.28922770326483
    - type: nAUC_mrr_std
      value: 83.63973501802224
  - task:
      type: PairClassification
    dataset:
      name: MTEB SprintDuplicateQuestions (default)
      type: mteb/sprintduplicatequestions-pairclassification
      config: default
      split: test
      revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46
    metrics:
    - type: cosine_accuracy
      value: 99.83861386138614
    - type: cosine_accuracy_threshold
      value: 74.75666999816895
    - type: cosine_ap
      value: 96.15132792066652
    - type: cosine_f1
      value: 91.84890656063618
    - type: cosine_f1_threshold
      value: 71.70594930648804
    - type: cosine_precision
      value: 91.30434782608695
    - type: cosine_recall
      value: 92.4
    - type: dot_accuracy
      value: 99.83861386138614
    - type: dot_accuracy_threshold
      value: 74.75666999816895
    - type: dot_ap
      value: 96.15132792066653
    - type: dot_f1
      value: 91.84890656063618
    - type: dot_f1_threshold
      value: 71.70596122741699
    - type: dot_precision
      value: 91.30434782608695
    - type: dot_recall
      value: 92.4
    - type: euclidean_accuracy
      value: 99.83861386138614
    - type: euclidean_accuracy_threshold
      value: 71.05395793914795
    - type: euclidean_ap
      value: 96.15132792066652
    - type: euclidean_f1
      value: 91.84890656063618
    - type: euclidean_f1_threshold
      value: 75.22505521774292
    - type: euclidean_precision
      value: 91.30434782608695
    - type: euclidean_recall
      value: 92.4
    - type: main_score
      value: 96.15132792066653
    - type: manhattan_accuracy
      value: 99.83564356435643
    - type: manhattan_accuracy_threshold
      value: 1547.6950645446777
    - type: manhattan_ap
      value: 96.06151211452136
    - type: manhattan_f1
      value: 91.61676646706587
    - type: manhattan_f1_threshold
      value: 1626.3608932495117
    - type: manhattan_precision
      value: 91.43426294820716
    - type: manhattan_recall
      value: 91.8
    - type: max_ap
      value: 96.15132792066653
    - type: max_f1
      value: 91.84890656063618
    - type: max_precision
      value: 91.43426294820716
    - type: max_recall
      value: 92.4
    - type: similarity_accuracy
      value: 99.83861386138614
    - type: similarity_accuracy_threshold
      value: 74.75666999816895
    - type: similarity_ap
      value: 96.15132792066652
    - type: similarity_f1
      value: 91.84890656063618
    - type: similarity_f1_threshold
      value: 71.70594930648804
    - type: similarity_precision
      value: 91.30434782608695
    - type: similarity_recall
      value: 92.4
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClustering (default)
      type: mteb/stackexchange-clustering
      config: default
      split: test
      revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259
    metrics:
    - type: main_score
      value: 61.24120328328453
    - type: v_measure
      value: 61.24120328328453
    - type: v_measure_std
      value: 3.9946560691100372
  - task:
      type: Clustering
    dataset:
      name: MTEB StackExchangeClusteringP2P (default)
      type: mteb/stackexchange-clustering-p2p
      config: default
      split: test
      revision: 815ca46b2622cec33ccafc3735d572c266efdb44
    metrics:
    - type: main_score
      value: 33.808268374864745
    - type: v_measure
      value: 33.808268374864745
    - type: v_measure_std
      value: 1.2212188701887239
  - task:
      type: Reranking
    dataset:
      name: MTEB StackOverflowDupQuestions (default)
      type: mteb/stackoverflowdupquestions-reranking
      config: default
      split: test
      revision: e185fbe320c72810689fc5848eb6114e1ef5ec69
    metrics:
    - type: main_score
      value: 52.19806018468037
    - type: map
      value: 52.19806018468037
    - type: mrr
      value: 52.98921462524404
    - type: nAUC_map_diff1
      value: 37.41443156995912
    - type: nAUC_map_max
      value: 9.410262727675603
    - type: nAUC_map_std
      value: 8.7094185014992
    - type: nAUC_mrr_diff1
      value: 37.78202772392581
    - type: nAUC_mrr_max
      value: 10.517635536565816
    - type: nAUC_mrr_std
      value: 8.509423813772491
  - task:
      type: Summarization
    dataset:
      name: MTEB SummEval (default)
      type: mteb/summeval
      config: default
      split: test
      revision: cda12ad7615edc362dbf25a00fdd61d3b1eaf93c
    metrics:
    - type: cosine_pearson
      value: 30.48413700430812
    - type: cosine_spearman
      value: 30.357162200875816
    - type: dot_pearson
      value: 30.484140144824938
    - type: dot_spearman
      value: 30.357162200875816
    - type: main_score
      value: 30.357162200875816
    - type: pearson
      value: 30.48413700430812
    - type: spearman
      value: 30.357162200875816
  - task:
      type: Classification
    dataset:
      name: MTEB ToxicConversationsClassification (default)
      type: mteb/toxic_conversations_50k
      config: default
      split: test
      revision: edfaf9da55d3dd50d43143d90c1ac476895ae6de
    metrics:
    - type: accuracy
      value: 66.8359375
    - type: ap
      value: 12.482653786025985
    - type: ap_weighted
      value: 12.482653786025985
    - type: f1
      value: 51.328608527332385
    - type: f1_weighted
      value: 74.07974463955398
    - type: main_score
      value: 66.8359375
  - task:
      type: Classification
    dataset:
      name: MTEB TweetSentimentExtractionClassification (default)
      type: mteb/tweet_sentiment_extraction
      config: default
      split: test
      revision: d604517c81ca91fe16a244d1248fc021f9ecee7a
    metrics:
    - type: accuracy
      value: 53.907753254103
    - type: f1
      value: 54.22707647269581
    - type: f1_weighted
      value: 53.611822984407695
    - type: main_score
      value: 53.907753254103
  - task:
      type: Clustering
    dataset:
      name: MTEB TwentyNewsgroupsClustering (default)
      type: mteb/twentynewsgroups-clustering
      config: default
      split: test
      revision: 6125ec4e24fa026cec8a478383ee943acfbd5449
    metrics:
    - type: main_score
      value: 38.1364789307295
    - type: v_measure
      value: 38.1364789307295
    - type: v_measure_std
      value: 2.0731634966352077
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterSemEval2015 (default)
      type: mteb/twittersemeval2015-pairclassification
      config: default
      split: test
      revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1
    metrics:
    - type: cosine_accuracy
      value: 82.66674614054956
    - type: cosine_accuracy_threshold
      value: 79.80123162269592
    - type: cosine_ap
      value: 63.28209719072804
    - type: cosine_f1
      value: 60.16389710903711
    - type: cosine_f1_threshold
      value: 72.22893834114075
    - type: cosine_precision
      value: 52.90232185748599
    - type: cosine_recall
      value: 69.73614775725594
    - type: dot_accuracy
      value: 82.66674614054956
    - type: dot_accuracy_threshold
      value: 79.8012375831604
    - type: dot_ap
      value: 63.282103870645166
    - type: dot_f1
      value: 60.16389710903711
    - type: dot_f1_threshold
      value: 72.22894430160522
    - type: dot_precision
      value: 52.90232185748599
    - type: dot_recall
      value: 69.73614775725594
    - type: euclidean_accuracy
      value: 82.66674614054956
    - type: euclidean_accuracy_threshold
      value: 63.55905532836914
    - type: euclidean_ap
      value: 63.282095399953164
    - type: euclidean_f1
      value: 60.16389710903711
    - type: euclidean_f1_threshold
      value: 74.5265781879425
    - type: euclidean_precision
      value: 52.90232185748599
    - type: euclidean_recall
      value: 69.73614775725594
    - type: main_score
      value: 63.282103870645166
    - type: manhattan_accuracy
      value: 82.74423317637242
    - type: manhattan_accuracy_threshold
      value: 1415.380859375
    - type: manhattan_ap
      value: 63.26931757839598
    - type: manhattan_f1
      value: 60.11014948859166
    - type: manhattan_f1_threshold
      value: 1632.522201538086
    - type: manhattan_precision
      value: 52.359506559624045
    - type: manhattan_recall
      value: 70.55408970976254
    - type: max_ap
      value: 63.282103870645166
    - type: max_f1
      value: 60.16389710903711
    - type: max_precision
      value: 52.90232185748599
    - type: max_recall
      value: 70.55408970976254
    - type: similarity_accuracy
      value: 82.66674614054956
    - type: similarity_accuracy_threshold
      value: 79.80123162269592
    - type: similarity_ap
      value: 63.28209719072804
    - type: similarity_f1
      value: 60.16389710903711
    - type: similarity_f1_threshold
      value: 72.22893834114075
    - type: similarity_precision
      value: 52.90232185748599
    - type: similarity_recall
      value: 69.73614775725594
  - task:
      type: PairClassification
    dataset:
      name: MTEB TwitterURLCorpus (default)
      type: mteb/twitterurlcorpus-pairclassification
      config: default
      split: test
      revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf
    metrics:
    - type: cosine_accuracy
      value: 88.10105949470253
    - type: cosine_accuracy_threshold
      value: 68.95147562026978
    - type: cosine_ap
      value: 84.65516103854583
    - type: cosine_f1
      value: 76.54581123301605
    - type: cosine_f1_threshold
      value: 63.92929553985596
    - type: cosine_precision
      value: 72.46526344751685
    - type: cosine_recall
      value: 81.11333538651063
    - type: dot_accuracy
      value: 88.10105949470253
    - type: dot_accuracy_threshold
      value: 68.95147562026978
    - type: dot_ap
      value: 84.65516301437592
    - type: dot_f1
      value: 76.54581123301605
    - type: dot_f1_threshold
      value: 63.92928957939148
    - type: dot_precision
      value: 72.46526344751685
    - type: dot_recall
      value: 81.11333538651063
    - type: euclidean_accuracy
      value: 88.10105949470253
    - type: euclidean_accuracy_threshold
      value: 78.80169153213501
    - type: euclidean_ap
      value: 84.65517268264233
    - type: euclidean_f1
      value: 76.54581123301605
    - type: euclidean_f1_threshold
      value: 84.93610620498657
    - type: euclidean_precision
      value: 72.46526344751685
    - type: euclidean_recall
      value: 81.11333538651063
    - type: main_score
      value: 84.65517268264233
    - type: manhattan_accuracy
      value: 88.08941669577366
    - type: manhattan_accuracy_threshold
      value: 1739.3169403076172
    - type: manhattan_ap
      value: 84.64592398855694
    - type: manhattan_f1
      value: 76.62890540443034
    - type: manhattan_f1_threshold
      value: 1861.344337463379
    - type: manhattan_precision
      value: 72.09775967413442
    - type: manhattan_recall
      value: 81.76778564829073
    - type: max_ap
      value: 84.65517268264233
    - type: max_f1
      value: 76.62890540443034
    - type: max_precision
      value: 72.46526344751685
    - type: max_recall
      value: 81.76778564829073
    - type: similarity_accuracy
      value: 88.10105949470253
    - type: similarity_accuracy_threshold
      value: 68.95147562026978
    - type: similarity_ap
      value: 84.65516103854583
    - type: similarity_f1
      value: 76.54581123301605
    - type: similarity_f1_threshold
      value: 63.92929553985596
    - type: similarity_precision
      value: 72.46526344751685
    - type: similarity_recall
      value: 81.11333538651063
---

# aimlresearch2023/snowflake-arctic-embed-m-v1.5-Q8_0-GGUF
This model was converted to GGUF format from [`Snowflake/snowflake-arctic-embed-m-v1.5`](https://huggingface.co/Snowflake/snowflake-arctic-embed-m-v1.5) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/Snowflake/snowflake-arctic-embed-m-v1.5) 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 aimlresearch2023/snowflake-arctic-embed-m-v1.5-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-v1.5-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo aimlresearch2023/snowflake-arctic-embed-m-v1.5-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-v1.5-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 aimlresearch2023/snowflake-arctic-embed-m-v1.5-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-v1.5-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo aimlresearch2023/snowflake-arctic-embed-m-v1.5-Q8_0-GGUF --hf-file snowflake-arctic-embed-m-v1.5-q8_0.gguf -c 2048
```