gguf language granite embeddings text-generation en base_model:ibm-granite/granite-embedding-30m-english base_model:quantized:ibm-granite/granite-embedding-30m-english license:apache-2.0 model-index endpoints_compatible region:us feature-extraction
---
base_model: ibm-granite/granite-embedding-30m-english
language:
- en
license: apache-2.0
pipeline_tag: text-generation
tags:
- language
- granite
- embeddings
quantized_by: bartowski
model-index:
- name: ibm-granite/granite-embedding-30m-english
  results:
  - task:
      type: Retrieval
    dataset:
      name: MTEB ArguaAna
      type: mteb/arguana
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.31792
    - type: map_at_10
      value: 0.47599
    - type: map_at_100
      value: 0.48425
    - type: map_at_1000
      value: 0.48427
    - type: map_at_3
      value: 0.42757
    - type: map_at_5
      value: 0.45634
    - type: mrr_at_1
      value: 0.32788
    - type: mrr_at_10
      value: 0.47974
    - type: mrr_at_100
      value: 0.48801
    - type: mrr_at_1000
      value: 0.48802
    - type: mrr_at_3
      value: 0.43065
    - type: mrr_at_5
      value: 0.45999
    - type: ndcg_at_1
      value: 0.31792
    - type: ndcg_at_10
      value: 0.56356
    - type: ndcg_at_100
      value: 0.59789
    - type: ndcg_at_1000
      value: 0.59857
    - type: ndcg_at_3
      value: 0.46453
    - type: ndcg_at_5
      value: 0.51623
    - type: precision_at_1
      value: 0.31792
    - type: precision_at_10
      value: 0.08428
    - type: precision_at_100
      value: 0.00991
    - type: precision_at_1000
      value: 0.001
    - type: precision_at_3
      value: 0.19061
    - type: precision_at_5
      value: 0.1394
    - type: recall_at_1
      value: 0.31792
    - type: recall_at_10
      value: 0.84282
    - type: recall_at_100
      value: 0.99075
    - type: recall_at_1000
      value: 0.99644
    - type: recall_at_3
      value: 0.57183
    - type: recall_at_5
      value: 0.69701
  - task:
      type: Retrieval
    dataset:
      name: MTEB ClimateFEVER
      type: mteb/climate-fever
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.13189
    - type: map_at_10
      value: 0.21789
    - type: map_at_100
      value: 0.2358
    - type: map_at_1000
      value: 0.23772
    - type: map_at_3
      value: 0.18513
    - type: map_at_5
      value: 0.20212
    - type: mrr_at_1
      value: 0.29837
    - type: mrr_at_10
      value: 0.41376
    - type: mrr_at_100
      value: 0.42282
    - type: mrr_at_1000
      value: 0.42319
    - type: mrr_at_3
      value: 0.38284
    - type: mrr_at_5
      value: 0.40301
    - type: ndcg_at_1
      value: 0.29837
    - type: ndcg_at_10
      value: 0.30263
    - type: ndcg_at_100
      value: 0.37228
    - type: ndcg_at_1000
      value: 0.40677
    - type: ndcg_at_3
      value: 0.25392
    - type: ndcg_at_5
      value: 0.27153
    - type: precision_at_1
      value: 0.29837
    - type: precision_at_10
      value: 0.09179
    - type: precision_at_100
      value: 0.01659
    - type: precision_at_1000
      value: 0.0023
    - type: precision_at_3
      value: 0.18545
    - type: precision_at_5
      value: 0.14241
    - type: recall_at_1
      value: 0.13189
    - type: recall_at_10
      value: 0.35355
    - type: recall_at_100
      value: 0.59255
    - type: recall_at_1000
      value: 0.78637
    - type: recall_at_3
      value: 0.23255
    - type: recall_at_5
      value: 0.28446
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackAndroidRetrieval
      type: mteb/cqadupstack-android
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.35797
    - type: map_at_10
      value: 0.47793
    - type: map_at_100
      value: 0.49422
    - type: map_at_1000
      value: 0.49546
    - type: map_at_3
      value: 0.44137
    - type: map_at_5
      value: 0.46063
    - type: mrr_at_1
      value: 0.44206
    - type: mrr_at_10
      value: 0.53808
    - type: mrr_at_100
      value: 0.5454
    - type: mrr_at_1000
      value: 0.54578
    - type: mrr_at_3
      value: 0.51431
    - type: mrr_at_5
      value: 0.5284
    - type: ndcg_at_1
      value: 0.44206
    - type: ndcg_at_10
      value: 0.54106
    - type: ndcg_at_100
      value: 0.59335
    - type: ndcg_at_1000
      value: 0.61015
    - type: ndcg_at_3
      value: 0.49365
    - type: ndcg_at_5
      value: 0.51429
    - type: precision_at_1
      value: 0.44206
    - type: precision_at_10
      value: 0.10443
    - type: precision_at_100
      value: 0.01631
    - type: precision_at_1000
      value: 0.00214
    - type: precision_at_3
      value: 0.23653
    - type: precision_at_5
      value: 0.1691
    - type: recall_at_1
      value: 0.35797
    - type: recall_at_10
      value: 0.65182
    - type: recall_at_100
      value: 0.86654
    - type: recall_at_1000
      value: 0.97131
    - type: recall_at_3
      value: 0.51224
    - type: recall_at_5
      value: 0.57219
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackEnglishRetrieval
      type: mteb/cqadupstack-english
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.32748
    - type: map_at_10
      value: 0.44138
    - type: map_at_100
      value: 0.45565
    - type: map_at_1000
      value: 0.45698
    - type: map_at_3
      value: 0.40916
    - type: map_at_5
      value: 0.42621
    - type: mrr_at_1
      value: 0.41274
    - type: mrr_at_10
      value: 0.5046
    - type: mrr_at_100
      value: 0.5107
    - type: mrr_at_1000
      value: 0.51109
    - type: mrr_at_3
      value: 0.48238
    - type: mrr_at_5
      value: 0.49563
    - type: ndcg_at_1
      value: 0.41274
    - type: ndcg_at_10
      value: 0.50251
    - type: ndcg_at_100
      value: 0.54725
    - type: ndcg_at_1000
      value: 0.56635
    - type: ndcg_at_3
      value: 0.46023
    - type: ndcg_at_5
      value: 0.47883
    - type: precision_at_1
      value: 0.41274
    - type: precision_at_10
      value: 0.09828
    - type: precision_at_100
      value: 0.01573
    - type: precision_at_1000
      value: 0.00202
    - type: precision_at_3
      value: 0.22718
    - type: precision_at_5
      value: 0.16064
    - type: recall_at_1
      value: 0.32748
    - type: recall_at_10
      value: 0.60322
    - type: recall_at_100
      value: 0.79669
    - type: recall_at_1000
      value: 0.9173
    - type: recall_at_3
      value: 0.47523
    - type: recall_at_5
      value: 0.52957
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGamingRetrieval
      type: mteb/cqadupstack-gaming
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.41126
    - type: map_at_10
      value: 0.53661
    - type: map_at_100
      value: 0.54588
    - type: map_at_1000
      value: 0.54638
    - type: map_at_3
      value: 0.50389
    - type: map_at_5
      value: 0.52286
    - type: mrr_at_1
      value: 0.47147
    - type: mrr_at_10
      value: 0.5685
    - type: mrr_at_100
      value: 0.57458
    - type: mrr_at_1000
      value: 0.57487
    - type: mrr_at_3
      value: 0.54431
    - type: mrr_at_5
      value: 0.55957
    - type: ndcg_at_1
      value: 0.47147
    - type: ndcg_at_10
      value: 0.59318
    - type: ndcg_at_100
      value: 0.62972
    - type: ndcg_at_1000
      value: 0.64033
    - type: ndcg_at_3
      value: 0.53969
    - type: ndcg_at_5
      value: 0.56743
    - type: precision_at_1
      value: 0.47147
    - type: precision_at_10
      value: 0.09549
    - type: precision_at_100
      value: 0.01224
    - type: precision_at_1000
      value: 0.00135
    - type: precision_at_3
      value: 0.24159
    - type: precision_at_5
      value: 0.16577
    - type: recall_at_1
      value: 0.41126
    - type: recall_at_10
      value: 0.72691
    - type: recall_at_100
      value: 0.88692
    - type: recall_at_1000
      value: 0.96232
    - type: recall_at_3
      value: 0.58374
    - type: recall_at_5
      value: 0.65226
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackGisRetrieval
      type: mteb/cqadupstack-gis
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.28464
    - type: map_at_10
      value: 0.3828
    - type: map_at_100
      value: 0.39277
    - type: map_at_1000
      value: 0.39355
    - type: map_at_3
      value: 0.35704
    - type: map_at_5
      value: 0.37116
    - type: mrr_at_1
      value: 0.30734
    - type: mrr_at_10
      value: 0.40422
    - type: mrr_at_100
      value: 0.41297
    - type: mrr_at_1000
      value: 0.41355
    - type: mrr_at_3
      value: 0.38136
    - type: mrr_at_5
      value: 0.39362
    - type: ndcg_at_1
      value: 0.30734
    - type: ndcg_at_10
      value: 0.43564
    - type: ndcg_at_100
      value: 0.48419
    - type: ndcg_at_1000
      value: 0.50404
    - type: ndcg_at_3
      value: 0.38672
    - type: ndcg_at_5
      value: 0.40954
    - type: precision_at_1
      value: 0.30734
    - type: precision_at_10
      value: 0.06633
    - type: precision_at_100
      value: 0.00956
    - type: precision_at_1000
      value: 0.00116
    - type: precision_at_3
      value: 0.16497
    - type: precision_at_5
      value: 0.11254
    - type: recall_at_1
      value: 0.28464
    - type: recall_at_10
      value: 0.57621
    - type: recall_at_100
      value: 0.7966
    - type: recall_at_1000
      value: 0.94633
    - type: recall_at_3
      value: 0.44588
    - type: recall_at_5
      value: 0.50031
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackMathematicaRetrieval
      type: mteb/cqadupstack-mathematica
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.18119
    - type: map_at_10
      value: 0.27055
    - type: map_at_100
      value: 0.28461
    - type: map_at_1000
      value: 0.28577
    - type: map_at_3
      value: 0.24341
    - type: map_at_5
      value: 0.25861
    - type: mrr_at_1
      value: 0.22886
    - type: mrr_at_10
      value: 0.32234
    - type: mrr_at_100
      value: 0.3328
    - type: mrr_at_1000
      value: 0.3334
    - type: mrr_at_3
      value: 0.29664
    - type: mrr_at_5
      value: 0.31107
    - type: ndcg_at_1
      value: 0.22886
    - type: ndcg_at_10
      value: 0.32749
    - type: ndcg_at_100
      value: 0.39095
    - type: ndcg_at_1000
      value: 0.41656
    - type: ndcg_at_3
      value: 0.27864
    - type: ndcg_at_5
      value: 0.30177
    - type: precision_at_1
      value: 0.22886
    - type: precision_at_10
      value: 0.06169
    - type: precision_at_100
      value: 0.0107
    - type: precision_at_1000
      value: 0.00143
    - type: precision_at_3
      value: 0.13682
    - type: precision_at_5
      value: 0.0995
    - type: recall_at_1
      value: 0.18119
    - type: recall_at_10
      value: 0.44983
    - type: recall_at_100
      value: 0.72396
    - type: recall_at_1000
      value: 0.90223
    - type: recall_at_3
      value: 0.31633
    - type: recall_at_5
      value: 0.37532
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackPhysicsRetrieval
      type: mteb/cqadupstack-physics
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.30517
    - type: map_at_10
      value: 0.42031
    - type: map_at_100
      value: 0.43415
    - type: map_at_1000
      value: 0.43525
    - type: map_at_3
      value: 0.38443
    - type: map_at_5
      value: 0.40685
    - type: mrr_at_1
      value: 0.38114
    - type: mrr_at_10
      value: 0.47783
    - type: mrr_at_100
      value: 0.48647
    - type: mrr_at_1000
      value: 0.48688
    - type: mrr_at_3
      value: 0.45172
    - type: mrr_at_5
      value: 0.46817
    - type: ndcg_at_1
      value: 0.38114
    - type: ndcg_at_10
      value: 0.4834
    - type: ndcg_at_100
      value: 0.53861
    - type: ndcg_at_1000
      value: 0.55701
    - type: ndcg_at_3
      value: 0.42986
    - type: ndcg_at_5
      value: 0.45893
    - type: precision_at_1
      value: 0.38114
    - type: precision_at_10
      value: 0.08893
    - type: precision_at_100
      value: 0.01375
    - type: precision_at_1000
      value: 0.00172
    - type: precision_at_3
      value: 0.20821
    - type: precision_at_5
      value: 0.15034
    - type: recall_at_1
      value: 0.30517
    - type: recall_at_10
      value: 0.61332
    - type: recall_at_100
      value: 0.84051
    - type: recall_at_1000
      value: 0.95826
    - type: recall_at_3
      value: 0.46015
    - type: recall_at_5
      value: 0.53801
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackProgrammersRetrieval
      type: mteb/cqadupstack-programmers
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.27396
    - type: map_at_10
      value: 0.38043
    - type: map_at_100
      value: 0.39341
    - type: map_at_1000
      value: 0.39454
    - type: map_at_3
      value: 0.34783
    - type: map_at_5
      value: 0.3663
    - type: mrr_at_1
      value: 0.34247
    - type: mrr_at_10
      value: 0.43681
    - type: mrr_at_100
      value: 0.4451
    - type: mrr_at_1000
      value: 0.44569
    - type: mrr_at_3
      value: 0.41172
    - type: mrr_at_5
      value: 0.42702
    - type: ndcg_at_1
      value: 0.34247
    - type: ndcg_at_10
      value: 0.44065
    - type: ndcg_at_100
      value: 0.49434
    - type: ndcg_at_1000
      value: 0.51682
    - type: ndcg_at_3
      value: 0.38976
    - type: ndcg_at_5
      value: 0.41332
    - type: precision_at_1
      value: 0.34247
    - type: precision_at_10
      value: 0.08059
    - type: precision_at_100
      value: 0.01258
    - type: precision_at_1000
      value: 0.00162
    - type: precision_at_3
      value: 0.1876
    - type: precision_at_5
      value: 0.13333
    - type: recall_at_1
      value: 0.27396
    - type: recall_at_10
      value: 0.56481
    - type: recall_at_100
      value: 0.79012
    - type: recall_at_1000
      value: 0.94182
    - type: recall_at_3
      value: 0.41785
    - type: recall_at_5
      value: 0.48303
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackStatsRetrieval
      type: mteb/cqadupstack-stats
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.25728
    - type: map_at_10
      value: 0.33903
    - type: map_at_100
      value: 0.34853
    - type: map_at_1000
      value: 0.34944
    - type: map_at_3
      value: 0.31268
    - type: map_at_5
      value: 0.32596
    - type: mrr_at_1
      value: 0.29141
    - type: mrr_at_10
      value: 0.36739
    - type: mrr_at_100
      value: 0.37545
    - type: mrr_at_1000
      value: 0.37608
    - type: mrr_at_3
      value: 0.34407
    - type: mrr_at_5
      value: 0.3568
    - type: ndcg_at_1
      value: 0.29141
    - type: ndcg_at_10
      value: 0.38596
    - type: ndcg_at_100
      value: 0.43375
    - type: ndcg_at_1000
      value: 0.45562
    - type: ndcg_at_3
      value: 0.33861
    - type: ndcg_at_5
      value: 0.35887
    - type: precision_at_1
      value: 0.29141
    - type: precision_at_10
      value: 0.06334
    - type: precision_at_100
      value: 0.00952
    - type: precision_at_1000
      value: 0.00121
    - type: precision_at_3
      value: 0.14826
    - type: precision_at_5
      value: 0.10429
    - type: recall_at_1
      value: 0.25728
    - type: recall_at_10
      value: 0.50121
    - type: recall_at_100
      value: 0.72382
    - type: recall_at_1000
      value: 0.88306
    - type: recall_at_3
      value: 0.36638
    - type: recall_at_5
      value: 0.41689
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackTexRetrieval
      type: mteb/cqadupstack-tex
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.19911
    - type: map_at_10
      value: 0.2856
    - type: map_at_100
      value: 0.29785
    - type: map_at_1000
      value: 0.29911
    - type: map_at_3
      value: 0.25875
    - type: map_at_5
      value: 0.2741
    - type: mrr_at_1
      value: 0.24054
    - type: mrr_at_10
      value: 0.32483
    - type: mrr_at_100
      value: 0.33464
    - type: mrr_at_1000
      value: 0.33534
    - type: mrr_at_3
      value: 0.30162
    - type: mrr_at_5
      value: 0.31506
    - type: ndcg_at_1
      value: 0.24054
    - type: ndcg_at_10
      value: 0.33723
    - type: ndcg_at_100
      value: 0.39362
    - type: ndcg_at_1000
      value: 0.42065
    - type: ndcg_at_3
      value: 0.29116
    - type: ndcg_at_5
      value: 0.31299
    - type: precision_at_1
      value: 0.24054
    - type: precision_at_10
      value: 0.06194
    - type: precision_at_100
      value: 0.01058
    - type: precision_at_1000
      value: 0.00148
    - type: precision_at_3
      value: 0.13914
    - type: precision_at_5
      value: 0.10076
    - type: recall_at_1
      value: 0.19911
    - type: recall_at_10
      value: 0.45183
    - type: recall_at_100
      value: 0.7025
    - type: recall_at_1000
      value: 0.89222
    - type: recall_at_3
      value: 0.32195
    - type: recall_at_5
      value: 0.37852
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackUnixRetrieval
      type: mteb/cqadupstack-unix
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.29819
    - type: map_at_10
      value: 0.40073
    - type: map_at_100
      value: 0.41289
    - type: map_at_1000
      value: 0.41375
    - type: map_at_3
      value: 0.36572
    - type: map_at_5
      value: 0.38386
    - type: mrr_at_1
      value: 0.35168
    - type: mrr_at_10
      value: 0.44381
    - type: mrr_at_100
      value: 0.45191
    - type: mrr_at_1000
      value: 0.45234
    - type: mrr_at_3
      value: 0.41402
    - type: mrr_at_5
      value: 0.43039
    - type: ndcg_at_1
      value: 0.35168
    - type: ndcg_at_10
      value: 0.46071
    - type: ndcg_at_100
      value: 0.51351
    - type: ndcg_at_1000
      value: 0.5317
    - type: ndcg_at_3
      value: 0.39972
    - type: ndcg_at_5
      value: 0.42586
    - type: precision_at_1
      value: 0.35168
    - type: precision_at_10
      value: 0.07985
    - type: precision_at_100
      value: 0.01185
    - type: precision_at_1000
      value: 0.00144
    - type: precision_at_3
      value: 0.18221
    - type: precision_at_5
      value: 0.12892
    - type: recall_at_1
      value: 0.29819
    - type: recall_at_10
      value: 0.60075
    - type: recall_at_100
      value: 0.82771
    - type: recall_at_1000
      value: 0.95219
    - type: recall_at_3
      value: 0.43245
    - type: recall_at_5
      value: 0.49931
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWebmastersRetrieval
      type: mteb/cqadupstack-webmasters
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.28409
    - type: map_at_10
      value: 0.37621
    - type: map_at_100
      value: 0.39233
    - type: map_at_1000
      value: 0.39471
    - type: map_at_3
      value: 0.34337
    - type: map_at_5
      value: 0.35985
    - type: mrr_at_1
      value: 0.33794
    - type: mrr_at_10
      value: 0.42349
    - type: mrr_at_100
      value: 0.43196
    - type: mrr_at_1000
      value: 0.43237
    - type: mrr_at_3
      value: 0.39526
    - type: mrr_at_5
      value: 0.41087
    - type: ndcg_at_1
      value: 0.33794
    - type: ndcg_at_10
      value: 0.43832
    - type: ndcg_at_100
      value: 0.49514
    - type: ndcg_at_1000
      value: 0.51742
    - type: ndcg_at_3
      value: 0.38442
    - type: ndcg_at_5
      value: 0.40737
    - type: precision_at_1
      value: 0.33794
    - type: precision_at_10
      value: 0.08597
    - type: precision_at_100
      value: 0.01652
    - type: precision_at_1000
      value: 0.00251
    - type: precision_at_3
      value: 0.17787
    - type: precision_at_5
      value: 0.13241
    - type: recall_at_1
      value: 0.28409
    - type: recall_at_10
      value: 0.55388
    - type: recall_at_100
      value: 0.81517
    - type: recall_at_1000
      value: 0.95038
    - type: recall_at_3
      value: 0.40133
    - type: recall_at_5
      value: 0.45913
  - task:
      type: Retrieval
    dataset:
      name: MTEB CQADupstackWordpressRetrieval
      type: mteb/cqadupstack-wordpress
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.24067
    - type: map_at_10
      value: 0.32184
    - type: map_at_100
      value: 0.33357
    - type: map_at_1000
      value: 0.33458
    - type: map_at_3
      value: 0.29492
    - type: map_at_5
      value: 0.3111
    - type: mrr_at_1
      value: 0.26248
    - type: mrr_at_10
      value: 0.34149
    - type: mrr_at_100
      value: 0.35189
    - type: mrr_at_1000
      value: 0.35251
    - type: mrr_at_3
      value: 0.31639
    - type: mrr_at_5
      value: 0.33182
    - type: ndcg_at_1
      value: 0.26248
    - type: ndcg_at_10
      value: 0.36889
    - type: ndcg_at_100
      value: 0.42426
    - type: ndcg_at_1000
      value: 0.44745
    - type: ndcg_at_3
      value: 0.31799
    - type: ndcg_at_5
      value: 0.34563
    - type: precision_at_1
      value: 0.26248
    - type: precision_at_10
      value: 0.05712
    - type: precision_at_100
      value: 0.00915
    - type: precision_at_1000
      value: 0.00123
    - type: precision_at_3
      value: 0.13309
    - type: precision_at_5
      value: 0.09649
    - type: recall_at_1
      value: 0.24067
    - type: recall_at_10
      value: 0.49344
    - type: recall_at_100
      value: 0.7412
    - type: recall_at_1000
      value: 0.91276
    - type: recall_at_3
      value: 0.36272
    - type: recall_at_5
      value: 0.4277
  - task:
      type: Retrieval
    dataset:
      name: MTEB DBPedia
      type: mteb/dbpedia
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.08651
    - type: map_at_10
      value: 0.17628
    - type: map_at_100
      value: 0.23354
    - type: map_at_1000
      value: 0.24827
    - type: map_at_3
      value: 0.1351
    - type: map_at_5
      value: 0.15468
    - type: mrr_at_1
      value: 0.645
    - type: mrr_at_10
      value: 0.71989
    - type: mrr_at_100
      value: 0.72332
    - type: mrr_at_1000
      value: 0.72346
    - type: mrr_at_3
      value: 0.7025
    - type: mrr_at_5
      value: 0.71275
    - type: ndcg_at_1
      value: 0.51375
    - type: ndcg_at_10
      value: 0.3596
    - type: ndcg_at_100
      value: 0.39878
    - type: ndcg_at_1000
      value: 0.47931
    - type: ndcg_at_3
      value: 0.41275
    - type: ndcg_at_5
      value: 0.38297
    - type: precision_at_1
      value: 0.645
    - type: precision_at_10
      value: 0.2745
    - type: precision_at_100
      value: 0.08405
    - type: precision_at_1000
      value: 0.01923
    - type: precision_at_3
      value: 0.44417
    - type: precision_at_5
      value: 0.366
    - type: recall_at_1
      value: 0.08651
    - type: recall_at_10
      value: 0.22416
    - type: recall_at_100
      value: 0.46381
    - type: recall_at_1000
      value: 0.71557
    - type: recall_at_3
      value: 0.14847
    - type: recall_at_5
      value: 0.1804
  - task:
      type: Retrieval
    dataset:
      name: MTEB FEVER
      type: mteb/fever
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.73211
    - type: map_at_10
      value: 0.81463
    - type: map_at_100
      value: 0.81622
    - type: map_at_1000
      value: 0.81634
    - type: map_at_3
      value: 0.805
    - type: map_at_5
      value: 0.81134
    - type: mrr_at_1
      value: 0.79088
    - type: mrr_at_10
      value: 0.86943
    - type: mrr_at_100
      value: 0.87017
    - type: mrr_at_1000
      value: 0.87018
    - type: mrr_at_3
      value: 0.86154
    - type: mrr_at_5
      value: 0.867
    - type: ndcg_at_1
      value: 0.79088
    - type: ndcg_at_10
      value: 0.85528
    - type: ndcg_at_100
      value: 0.86134
    - type: ndcg_at_1000
      value: 0.86367
    - type: ndcg_at_3
      value: 0.83943
    - type: ndcg_at_5
      value: 0.84878
    - type: precision_at_1
      value: 0.79088
    - type: precision_at_10
      value: 0.10132
    - type: precision_at_100
      value: 0.01055
    - type: precision_at_1000
      value: 0.00109
    - type: precision_at_3
      value: 0.31963
    - type: precision_at_5
      value: 0.19769
    - type: recall_at_1
      value: 0.73211
    - type: recall_at_10
      value: 0.92797
    - type: recall_at_100
      value: 0.95263
    - type: recall_at_1000
      value: 0.96738
    - type: recall_at_3
      value: 0.88328
    - type: recall_at_5
      value: 0.90821
  - task:
      type: Retrieval
    dataset:
      name: MTEB FiQA2018
      type: mteb/fiqa
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.18311
    - type: map_at_10
      value: 0.29201
    - type: map_at_100
      value: 0.3093
    - type: map_at_1000
      value: 0.31116
    - type: map_at_3
      value: 0.24778
    - type: map_at_5
      value: 0.27453
    - type: mrr_at_1
      value: 0.35494
    - type: mrr_at_10
      value: 0.44489
    - type: mrr_at_100
      value: 0.4532
    - type: mrr_at_1000
      value: 0.45369
    - type: mrr_at_3
      value: 0.41667
    - type: mrr_at_5
      value: 0.43418
    - type: ndcg_at_1
      value: 0.35494
    - type: ndcg_at_10
      value: 0.36868
    - type: ndcg_at_100
      value: 0.43463
    - type: ndcg_at_1000
      value: 0.46766
    - type: ndcg_at_3
      value: 0.32305
    - type: ndcg_at_5
      value: 0.34332
    - type: precision_at_1
      value: 0.35494
    - type: precision_at_10
      value: 0.10324
    - type: precision_at_100
      value: 0.01707
    - type: precision_at_1000
      value: 0.00229
    - type: precision_at_3
      value: 0.21142
    - type: precision_at_5
      value: 0.16327
    - type: recall_at_1
      value: 0.18311
    - type: recall_at_10
      value: 0.43881
    - type: recall_at_100
      value: 0.68593
    - type: recall_at_1000
      value: 0.8855
    - type: recall_at_3
      value: 0.28824
    - type: recall_at_5
      value: 0.36178
  - task:
      type: Retrieval
    dataset:
      name: MTEB HotpotQA
      type: mteb/hotpotqa
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.36766
    - type: map_at_10
      value: 0.53639
    - type: map_at_100
      value: 0.54532
    - type: map_at_1000
      value: 0.54608
    - type: map_at_3
      value: 0.50427
    - type: map_at_5
      value: 0.5245
    - type: mrr_at_1
      value: 0.73531
    - type: mrr_at_10
      value: 0.80104
    - type: mrr_at_100
      value: 0.80341
    - type: mrr_at_1000
      value: 0.80351
    - type: mrr_at_3
      value: 0.78949
    - type: mrr_at_5
      value: 0.79729
    - type: ndcg_at_1
      value: 0.73531
    - type: ndcg_at_10
      value: 0.62918
    - type: ndcg_at_100
      value: 0.66056
    - type: ndcg_at_1000
      value: 0.67554
    - type: ndcg_at_3
      value: 0.58247
    - type: ndcg_at_5
      value: 0.60905
    - type: precision_at_1
      value: 0.73531
    - type: precision_at_10
      value: 0.1302
    - type: precision_at_100
      value: 0.01546
    - type: precision_at_1000
      value: 0.00175
    - type: precision_at_3
      value: 0.36556
    - type: precision_at_5
      value: 0.24032
    - type: recall_at_1
      value: 0.36766
    - type: recall_at_10
      value: 0.65098
    - type: recall_at_100
      value: 0.77306
    - type: recall_at_1000
      value: 0.87252
    - type: recall_at_3
      value: 0.54835
    - type: recall_at_5
      value: 0.60081
  - task:
      type: Retrieval
    dataset:
      name: MTEB MSMARCO
      type: mteb/msmarco
      config: default
      split: dev
    metrics:
    - type: map_at_1
      value: 0.14654
    - type: map_at_10
      value: 0.2472
    - type: map_at_100
      value: 0.25994
    - type: map_at_1000
      value: 0.26067
    - type: map_at_3
      value: 0.21234
    - type: map_at_5
      value: 0.2319
    - type: mrr_at_1
      value: 0.15086
    - type: mrr_at_10
      value: 0.25184
    - type: mrr_at_100
      value: 0.26422
    - type: mrr_at_1000
      value: 0.26489
    - type: mrr_at_3
      value: 0.21731
    - type: mrr_at_5
      value: 0.23674
    - type: ndcg_at_1
      value: 0.15086
    - type: ndcg_at_10
      value: 0.30711
    - type: ndcg_at_100
      value: 0.37221
    - type: ndcg_at_1000
      value: 0.39133
    - type: ndcg_at_3
      value: 0.23567
    - type: ndcg_at_5
      value: 0.27066
    - type: precision_at_1
      value: 0.15086
    - type: precision_at_10
      value: 0.05132
    - type: precision_at_100
      value: 0.00845
    - type: precision_at_1000
      value: 0.00101
    - type: precision_at_3
      value: 0.10277
    - type: precision_at_5
      value: 0.07923
    - type: recall_at_1
      value: 0.14654
    - type: recall_at_10
      value: 0.49341
    - type: recall_at_100
      value: 0.80224
    - type: recall_at_1000
      value: 0.95037
    - type: recall_at_3
      value: 0.29862
    - type: recall_at_5
      value: 0.38274
  - task:
      type: Retrieval
    dataset:
      name: MTEB NFCorpus
      type: mteb/nfcorpus
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.05452
    - type: map_at_10
      value: 0.12758
    - type: map_at_100
      value: 0.1593
    - type: map_at_1000
      value: 0.17422
    - type: map_at_3
      value: 0.0945
    - type: map_at_5
      value: 0.1092
    - type: mrr_at_1
      value: 0.43963
    - type: mrr_at_10
      value: 0.53237
    - type: mrr_at_100
      value: 0.53777
    - type: mrr_at_1000
      value: 0.53822
    - type: mrr_at_3
      value: 0.51445
    - type: mrr_at_5
      value: 0.52466
    - type: ndcg_at_1
      value: 0.41486
    - type: ndcg_at_10
      value: 0.33737
    - type: ndcg_at_100
      value: 0.30886
    - type: ndcg_at_1000
      value: 0.40018
    - type: ndcg_at_3
      value: 0.39324
    - type: ndcg_at_5
      value: 0.36949
    - type: precision_at_1
      value: 0.43344
    - type: precision_at_10
      value: 0.24799
    - type: precision_at_100
      value: 0.07895
    - type: precision_at_1000
      value: 0.02091
    - type: precision_at_3
      value: 0.37152
    - type: precision_at_5
      value: 0.31703
    - type: recall_at_1
      value: 0.05452
    - type: recall_at_10
      value: 0.1712
    - type: recall_at_100
      value: 0.30719
    - type: recall_at_1000
      value: 0.62766
    - type: recall_at_3
      value: 0.10733
    - type: recall_at_5
      value: 0.13553
  - task:
      type: Retrieval
    dataset:
      name: MTEB NQ
      type: mteb/nq
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.29022
    - type: map_at_10
      value: 0.4373
    - type: map_at_100
      value: 0.44849
    - type: map_at_1000
      value: 0.44877
    - type: map_at_3
      value: 0.39045
    - type: map_at_5
      value: 0.4186
    - type: mrr_at_1
      value: 0.32793
    - type: mrr_at_10
      value: 0.46243
    - type: mrr_at_100
      value: 0.47083
    - type: mrr_at_1000
      value: 0.47101
    - type: mrr_at_3
      value: 0.42261
    - type: mrr_at_5
      value: 0.44775
    - type: ndcg_at_1
      value: 0.32793
    - type: ndcg_at_10
      value: 0.51631
    - type: ndcg_at_100
      value: 0.56287
    - type: ndcg_at_1000
      value: 0.56949
    - type: ndcg_at_3
      value: 0.42782
    - type: ndcg_at_5
      value: 0.47554
    - type: precision_at_1
      value: 0.32793
    - type: precision_at_10
      value: 0.08737
    - type: precision_at_100
      value: 0.01134
    - type: precision_at_1000
      value: 0.0012
    - type: precision_at_3
      value: 0.19583
    - type: precision_at_5
      value: 0.14484
    - type: recall_at_1
      value: 0.29022
    - type: recall_at_10
      value: 0.73325
    - type: recall_at_100
      value: 0.93455
    - type: recall_at_1000
      value: 0.98414
    - type: recall_at_3
      value: 0.50406
    - type: recall_at_5
      value: 0.6145
  - task:
      type: Retrieval
    dataset:
      name: MTEB QuoraRetrieval
      type: mteb/quora
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.68941
    - type: map_at_10
      value: 0.82641
    - type: map_at_100
      value: 0.83317
    - type: map_at_1000
      value: 0.83337
    - type: map_at_3
      value: 0.79604
    - type: map_at_5
      value: 0.81525
    - type: mrr_at_1
      value: 0.7935
    - type: mrr_at_10
      value: 0.85969
    - type: mrr_at_100
      value: 0.86094
    - type: mrr_at_1000
      value: 0.86095
    - type: mrr_at_3
      value: 0.84852
    - type: mrr_at_5
      value: 0.85627
    - type: ndcg_at_1
      value: 0.7936
    - type: ndcg_at_10
      value: 0.86687
    - type: ndcg_at_100
      value: 0.88094
    - type: ndcg_at_1000
      value: 0.88243
    - type: ndcg_at_3
      value: 0.83538
    - type: ndcg_at_5
      value: 0.85308
    - type: precision_at_1
      value: 0.7936
    - type: precision_at_10
      value: 0.13145
    - type: precision_at_100
      value: 0.01517
    - type: precision_at_1000
      value: 0.00156
    - type: precision_at_3
      value: 0.36353
    - type: precision_at_5
      value: 0.24044
    - type: recall_at_1
      value: 0.68941
    - type: recall_at_10
      value: 0.94407
    - type: recall_at_100
      value: 0.99226
    - type: recall_at_1000
      value: 0.99958
    - type: recall_at_3
      value: 0.85502
    - type: recall_at_5
      value: 0.90372
  - task:
      type: Retrieval
    dataset:
      name: MTEB SCIDOCS
      type: mteb/scidocs
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.04988
    - type: map_at_10
      value: 0.13553
    - type: map_at_100
      value: 0.16136
    - type: map_at_1000
      value: 0.16512
    - type: map_at_3
      value: 0.09439
    - type: map_at_5
      value: 0.1146
    - type: mrr_at_1
      value: 0.246
    - type: mrr_at_10
      value: 0.36792
    - type: mrr_at_100
      value: 0.37973
    - type: mrr_at_1000
      value: 0.38011
    - type: mrr_at_3
      value: 0.33117
    - type: mrr_at_5
      value: 0.35172
    - type: ndcg_at_1
      value: 0.246
    - type: ndcg_at_10
      value: 0.22542
    - type: ndcg_at_100
      value: 0.32326
    - type: ndcg_at_1000
      value: 0.3828
    - type: ndcg_at_3
      value: 0.20896
    - type: ndcg_at_5
      value: 0.18497
    - type: precision_at_1
      value: 0.246
    - type: precision_at_10
      value: 0.1194
    - type: precision_at_100
      value: 0.02616
    - type: precision_at_1000
      value: 0.00404
    - type: precision_at_3
      value: 0.198
    - type: precision_at_5
      value: 0.1654
    - type: recall_at_1
      value: 0.04988
    - type: recall_at_10
      value: 0.24212
    - type: recall_at_100
      value: 0.53105
    - type: recall_at_1000
      value: 0.82022
    - type: recall_at_3
      value: 0.12047
    - type: recall_at_5
      value: 0.16777
  - task:
      type: Retrieval
    dataset:
      name: MTEB SciFact
      type: mteb/scifact
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.56578
    - type: map_at_10
      value: 0.66725
    - type: map_at_100
      value: 0.67379
    - type: map_at_1000
      value: 0.674
    - type: map_at_3
      value: 0.63416
    - type: map_at_5
      value: 0.6577
    - type: mrr_at_1
      value: 0.59333
    - type: mrr_at_10
      value: 0.67533
    - type: mrr_at_100
      value: 0.68062
    - type: mrr_at_1000
      value: 0.68082
    - type: mrr_at_3
      value: 0.64944
    - type: mrr_at_5
      value: 0.66928
    - type: ndcg_at_1
      value: 0.59333
    - type: ndcg_at_10
      value: 0.7127
    - type: ndcg_at_100
      value: 0.73889
    - type: ndcg_at_1000
      value: 0.7441
    - type: ndcg_at_3
      value: 0.65793
    - type: ndcg_at_5
      value: 0.69429
    - type: precision_at_1
      value: 0.59333
    - type: precision_at_10
      value: 0.096
    - type: precision_at_100
      value: 0.01087
    - type: precision_at_1000
      value: 0.00113
    - type: precision_at_3
      value: 0.25556
    - type: precision_at_5
      value: 0.17667
    - type: recall_at_1
      value: 0.56578
    - type: recall_at_10
      value: 0.842
    - type: recall_at_100
      value: 0.95667
    - type: recall_at_1000
      value: 0.99667
    - type: recall_at_3
      value: 0.70072
    - type: recall_at_5
      value: 0.79011
  - task:
      type: Retrieval
    dataset:
      name: MTEB Touche2020
      type: mteb/touche2020
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.01976
    - type: map_at_10
      value: 0.09688
    - type: map_at_100
      value: 0.15117
    - type: map_at_1000
      value: 0.16769
    - type: map_at_3
      value: 0.04589
    - type: map_at_5
      value: 0.06556
    - type: mrr_at_1
      value: 0.26531
    - type: mrr_at_10
      value: 0.43863
    - type: mrr_at_100
      value: 0.44767
    - type: mrr_at_1000
      value: 0.44767
    - type: mrr_at_3
      value: 0.39116
    - type: mrr_at_5
      value: 0.41156
    - type: ndcg_at_1
      value: 0.23469
    - type: ndcg_at_10
      value: 0.24029
    - type: ndcg_at_100
      value: 0.34425
    - type: ndcg_at_1000
      value: 0.46907
    - type: ndcg_at_3
      value: 0.25522
    - type: ndcg_at_5
      value: 0.24333
    - type: precision_at_1
      value: 0.26531
    - type: precision_at_10
      value: 0.22449
    - type: precision_at_100
      value: 0.07122
    - type: precision_at_1000
      value: 0.01527
    - type: precision_at_3
      value: 0.27891
    - type: precision_at_5
      value: 0.25714
    - type: recall_at_1
      value: 0.01976
    - type: recall_at_10
      value: 0.16633
    - type: recall_at_100
      value: 0.4561
    - type: recall_at_1000
      value: 0.82481
    - type: recall_at_3
      value: 0.06101
    - type: recall_at_5
      value: 0.0968
  - task:
      type: Retrieval
    dataset:
      name: MTEB TRECCOVID
      type: mteb/trec-covid
      config: default
      split: test
    metrics:
    - type: map_at_1
      value: 0.00211
    - type: map_at_10
      value: 0.01526
    - type: map_at_100
      value: 0.08863
    - type: map_at_1000
      value: 0.23162
    - type: map_at_3
      value: 0.00555
    - type: map_at_5
      value: 0.00873
    - type: mrr_at_1
      value: 0.76
    - type: mrr_at_10
      value: 0.8485
    - type: mrr_at_100
      value: 0.8485
    - type: mrr_at_1000
      value: 0.8485
    - type: mrr_at_3
      value: 0.84
    - type: mrr_at_5
      value: 0.844
    - type: ndcg_at_1
      value: 0.7
    - type: ndcg_at_10
      value: 0.63098
    - type: ndcg_at_100
      value: 0.49847
    - type: ndcg_at_1000
      value: 0.48395
    - type: ndcg_at_3
      value: 0.68704
    - type: ndcg_at_5
      value: 0.67533
    - type: precision_at_1
      value: 0.76
    - type: precision_at_10
      value: 0.66
    - type: precision_at_100
      value: 0.5134
    - type: precision_at_1000
      value: 0.2168
    - type: precision_at_3
      value: 0.72667
    - type: precision_at_5
      value: 0.716
    - type: recall_at_1
      value: 0.00211
    - type: recall_at_10
      value: 0.01748
    - type: recall_at_100
      value: 0.12448
    - type: recall_at_1000
      value: 0.46795
    - type: recall_at_3
      value: 0.00593
    - type: recall_at_5
      value: 0.00962
---
## 💫 Community Model> granite embedding 30m english by Ibm-Granite

*👾 [LM Studio](https://lmstudio.ai) Community models highlights program. Highlighting new & noteworthy models by the community. Join the conversation on [Discord](https://discord.gg/aPQfnNkxGC)*.

**Model creator:** [ibm-granite](https://huggingface.co/ibm-granite)<br>
**Original model**: [granite-embedding-30m-english](https://huggingface.co/ibm-granite/granite-embedding-30m-english)<br>
**GGUF quantization:** provided by [bartowski](https://huggingface.co/bartowski) based on `llama.cpp` release [b4381](https://github.com/ggerganov/llama.cpp/releases/tag/b4381)<br>

## Technical Details

Embedding model with vector size 384

Max length of 512 tokens

30 million param model for extremely fast performance

English only

## Special thanks

🙏 Special thanks to [Georgi Gerganov](https://github.com/ggerganov) and the whole team working on [llama.cpp](https://github.com/ggerganov/llama.cpp/) for making all of this possible.

## Disclaimers

LM Studio is not the creator, originator, or owner of any Model featured in the Community Model Program. Each Community Model is created and provided by third parties. LM Studio does not endorse, support, represent or guarantee the completeness, truthfulness, accuracy, or reliability of any Community Model.  You understand that Community Models can produce content that might be offensive, harmful, inaccurate or otherwise inappropriate, or deceptive. Each Community Model is the sole responsibility of the person or entity who originated such Model. LM Studio may not monitor or control the Community Models and cannot, and does not, take responsibility for any such Model. LM Studio disclaims all warranties or guarantees about the accuracy, reliability or benefits of the Community Models.  LM Studio further disclaims any warranty that the Community Model will meet your requirements, be secure, uninterrupted or available at any time or location, or error-free, viruses-free, or that any errors will be corrected, or otherwise. You will be solely responsible for any damage resulting from your use of or access to the Community Models, your downloading of any Community Model, or use of any other Community Model provided by or through LM Studio.
