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README.md

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+---
+license: apache-2.0
+tags:
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+- mteb
+- arctic
+- snowflake-arctic-embed
+- transformers.js
+- llama-cpp
+- gguf-my-repo
+base_model: Snowflake/snowflake-arctic-embed-l
+pipeline_tag: sentence-similarity
+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:
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+ value: 28.247
+ - type: map_at_10
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+ - type: map_at_100
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+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: map_at_5
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
+ value: 10.491
+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - 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:
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+ value: 22.45
+ - type: map_at_10
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+ - type: map_at_100
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+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: map_at_5
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - 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:
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+ value: 32.123000000000005
+ - type: map_at_10
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+ - type: map_at_100
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+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: map_at_5
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+ - type: mrr_at_1
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - 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:
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+ value: 33.196999999999996
+ - type: map_at_10
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+ - type: map_at_100
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+ - type: map_at_1000
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+ - type: map_at_5
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
+ value: 0.25
+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - 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
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+ - type: map_at_100
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+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: map_at_5
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - 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
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+ - type: map_at_100
+ value: 31.463
+ - type: map_at_1000
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+ - type: map_at_3
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+ - type: map_at_5
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - type: recall_at_1000
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+ - 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
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+ - type: map_at_5
+ value: 18.199
+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
+ value: 12.005
+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - 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
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - 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
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - 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
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+ - 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
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+ - type: map_at_5
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+ - type: mrr_at_1
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+ - type: mrr_at_10
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
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+ - type: recall_at_1
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+ - type: recall_at_10
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+ - type: recall_at_100
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+ - 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
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+ - 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
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+ - type: mrr_at_100
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+ - type: mrr_at_1000
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+ - type: mrr_at_3
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+ - type: mrr_at_5
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+ - type: ndcg_at_1
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
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+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
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+ - type: precision_at_3
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+ - type: precision_at_5
+ value: 10.796999999999999
+ - type: recall_at_1
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+ - type: recall_at_10
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+ - 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
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+ - type: ndcg_at_10
+ value: 63.108
+ - type: ndcg_at_100
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+ - type: ndcg_at_1000
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+ - type: ndcg_at_3
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+ - type: ndcg_at_5
+ value: 59.681
+ - type: precision_at_1
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+ - 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
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+ - 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:
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+ 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
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+ - 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
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+ - 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
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+ - type: ndcg_at_10
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+ - type: ndcg_at_100
+ value: 29.396
+ - type: ndcg_at_1000
+ value: 34.849999999999994
+ - type: ndcg_at_3
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+ - type: ndcg_at_5
+ value: 18.086
+ - type: precision_at_1
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+ - type: precision_at_10
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+ - type: precision_at_100
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+ - type: precision_at_1000
+ value: 0.358
+ - type: precision_at_3
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+ - 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:
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+ value: 69.66387868726018
+ - type: cos_sim_spearman
+ value: 67.85470749045027
+ - type: euclidean_pearson
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+ - type: euclidean_spearman
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+ - 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:
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+ 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
+---
+
+# radia/snowflake-arctic-embed-l-Q4_K_M-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 --hf-repo radia/snowflake-arctic-embed-l-Q4_K_M-GGUF --hf-file snowflake-arctic-embed-l-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo radia/snowflake-arctic-embed-l-Q4_K_M-GGUF --hf-file snowflake-arctic-embed-l-q4_k_m.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.
+```
+./main --hf-repo radia/snowflake-arctic-embed-l-Q4_K_M-GGUF --hf-file snowflake-arctic-embed-l-q4_k_m.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./server --hf-repo radia/snowflake-arctic-embed-l-Q4_K_M-GGUF --hf-file snowflake-arctic-embed-l-q4_k_m.gguf -c 2048
+```