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@@ -1,1790 +1,11 @@
 ---
 quantized_by: bartowski
 pipeline_tag: text-generation
-language:
-- en
-tags:
-- language
-- granite
-- embeddings
-license: apache-2.0
-base_model: ibm-granite/granite-embedding-30m-english
-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
 ---
 
 ## Llamacpp Static Quantizations of granite-embedding-30m-english
 
-Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b4341">b4341</a> for quantization.
+Using <a href="https://github.com/ggerganov/llama.cpp/">llama.cpp</a> release <a href="https://github.com/ggerganov/llama.cpp/releases/tag/b4381">b4381</a> for quantization.
 
 Original model: https://huggingface.co/ibm-granite/granite-embedding-30m-english
 
@@ -1794,6 +15,10 @@ Run them in [LM Studio](https://lmstudio.ai/)
 
 No prompt format found, check original model page
 
+## What's new:
+
+Fix tokenizer
+
 ## Download a file (not the whole branch) from below:
 
 | Filename | Quant type | File Size | Split | Description |
@@ -1813,6 +38,7 @@ No prompt format found, check original model page
 | [granite-embedding-30m-english-IQ4_XS.gguf](https://huggingface.co/bartowski/granite-embedding-30m-english-GGUF/blob/main/granite-embedding-30m-english-IQ4_XS.gguf) | IQ4_XS | 0.03GB | false | Decent quality, smaller than Q4_K_S with similar performance, *recommended*. |
 | [granite-embedding-30m-english-Q3_K_XL.gguf](https://huggingface.co/bartowski/granite-embedding-30m-english-GGUF/blob/main/granite-embedding-30m-english-Q3_K_XL.gguf) | Q3_K_XL | 0.03GB | false | Uses Q8_0 for embed and output weights. Lower quality but usable, good for low RAM availability. |
 | [granite-embedding-30m-english-Q3_K_L.gguf](https://huggingface.co/bartowski/granite-embedding-30m-english-GGUF/blob/main/granite-embedding-30m-english-Q3_K_L.gguf) | Q3_K_L | 0.03GB | false | Lower quality but usable, good for low RAM availability. |
+| [granite-embedding-30m-english-Q3_K_M.gguf](https://huggingface.co/bartowski/granite-embedding-30m-english-GGUF/blob/main/granite-embedding-30m-english-Q3_K_M.gguf) | Q3_K_M | 0.03GB | false | Low quality. |
 | [granite-embedding-30m-english-IQ3_M.gguf](https://huggingface.co/bartowski/granite-embedding-30m-english-GGUF/blob/main/granite-embedding-30m-english-IQ3_M.gguf) | IQ3_M | 0.03GB | false | Medium-low quality, new method with decent performance comparable to Q3_K_M. |
 
 ## Embed/output weights