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+---
+tags:
+- sentence-transformers
+- feature-extraction
+- sentence-similarity
+- mteb
+- RAG
+- llama-cpp
+- gguf-my-repo
+license: apache-2.0
+language:
+- zh
+- en
+pipeline_tag: feature-extraction
+base_model: DMetaSoul/Dmeta-embedding-zh
+model-index:
+- name: Dmeta-embedding
+  results:
+  - task:
+      type: STS
+    dataset:
+      name: MTEB AFQMC
+      type: C-MTEB/AFQMC
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 65.60825224706932
+    - type: cos_sim_spearman
+      value: 71.12862586297193
+    - type: euclidean_pearson
+      value: 70.18130275750404
+    - type: euclidean_spearman
+      value: 71.12862586297193
+    - type: manhattan_pearson
+      value: 70.14470398075396
+    - type: manhattan_spearman
+      value: 71.05226975911737
+  - task:
+      type: STS
+    dataset:
+      name: MTEB ATEC
+      type: C-MTEB/ATEC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 65.52386345655479
+    - type: cos_sim_spearman
+      value: 64.64245253181382
+    - type: euclidean_pearson
+      value: 73.20157662981914
+    - type: euclidean_spearman
+      value: 64.64245253178956
+    - type: manhattan_pearson
+      value: 73.22837571756348
+    - type: manhattan_spearman
+      value: 64.62632334391418
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB AmazonReviewsClassification (zh)
+      type: mteb/amazon_reviews_multi
+      config: zh
+      split: test
+      revision: 1399c76144fd37290681b995c656ef9b2e06e26d
+    metrics:
+    - type: accuracy
+      value: 44.925999999999995
+    - type: f1
+      value: 42.82555191308971
+  - task:
+      type: STS
+    dataset:
+      name: MTEB BQ
+      type: C-MTEB/BQ
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 71.35236446393156
+    - type: cos_sim_spearman
+      value: 72.29629643702184
+    - type: euclidean_pearson
+      value: 70.94570179874498
+    - type: euclidean_spearman
+      value: 72.29629297226953
+    - type: manhattan_pearson
+      value: 70.84463025501125
+    - type: manhattan_spearman
+      value: 72.24527021975821
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB CLSClusteringP2P
+      type: C-MTEB/CLSClusteringP2P
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 40.24232916894152
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB CLSClusteringS2S
+      type: C-MTEB/CLSClusteringS2S
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 39.167806226929706
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB CMedQAv1
+      type: C-MTEB/CMedQAv1-reranking
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map
+      value: 88.48837920106357
+    - type: mrr
+      value: 90.36861111111111
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB CMedQAv2
+      type: C-MTEB/CMedQAv2-reranking
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: map
+      value: 89.17878171657071
+    - type: mrr
+      value: 91.35805555555555
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CmedqaRetrieval
+      type: C-MTEB/CmedqaRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 25.751
+    - type: map_at_10
+      value: 38.946
+    - type: map_at_100
+      value: 40.855000000000004
+    - type: map_at_1000
+      value: 40.953
+    - type: map_at_3
+      value: 34.533
+    - type: map_at_5
+      value: 36.905
+    - type: mrr_at_1
+      value: 39.235
+    - type: mrr_at_10
+      value: 47.713
+    - type: mrr_at_100
+      value: 48.71
+    - type: mrr_at_1000
+      value: 48.747
+    - type: mrr_at_3
+      value: 45.086
+    - type: mrr_at_5
+      value: 46.498
+    - type: ndcg_at_1
+      value: 39.235
+    - type: ndcg_at_10
+      value: 45.831
+    - type: ndcg_at_100
+      value: 53.162
+    - type: ndcg_at_1000
+      value: 54.800000000000004
+    - type: ndcg_at_3
+      value: 40.188
+    - type: ndcg_at_5
+      value: 42.387
+    - type: precision_at_1
+      value: 39.235
+    - type: precision_at_10
+      value: 10.273
+    - type: precision_at_100
+      value: 1.627
+    - type: precision_at_1000
+      value: 0.183
+    - type: precision_at_3
+      value: 22.772000000000002
+    - type: precision_at_5
+      value: 16.524
+    - type: recall_at_1
+      value: 25.751
+    - type: recall_at_10
+      value: 57.411
+    - type: recall_at_100
+      value: 87.44
+    - type: recall_at_1000
+      value: 98.386
+    - type: recall_at_3
+      value: 40.416000000000004
+    - type: recall_at_5
+      value: 47.238
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB Cmnli
+      type: C-MTEB/CMNLI
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 83.59591100420926
+    - type: cos_sim_ap
+      value: 90.65538153970263
+    - type: cos_sim_f1
+      value: 84.76466651795673
+    - type: cos_sim_precision
+      value: 81.04073363190446
+    - type: cos_sim_recall
+      value: 88.84732288987608
+    - type: dot_accuracy
+      value: 83.59591100420926
+    - type: dot_ap
+      value: 90.64355541781003
+    - type: dot_f1
+      value: 84.76466651795673
+    - type: dot_precision
+      value: 81.04073363190446
+    - type: dot_recall
+      value: 88.84732288987608
+    - type: euclidean_accuracy
+      value: 83.59591100420926
+    - type: euclidean_ap
+      value: 90.6547878194287
+    - type: euclidean_f1
+      value: 84.76466651795673
+    - type: euclidean_precision
+      value: 81.04073363190446
+    - type: euclidean_recall
+      value: 88.84732288987608
+    - type: manhattan_accuracy
+      value: 83.51172579675286
+    - type: manhattan_ap
+      value: 90.59941589844144
+    - type: manhattan_f1
+      value: 84.51827242524917
+    - type: manhattan_precision
+      value: 80.28613507258574
+    - type: manhattan_recall
+      value: 89.22141688099134
+    - type: max_accuracy
+      value: 83.59591100420926
+    - type: max_ap
+      value: 90.65538153970263
+    - type: max_f1
+      value: 84.76466651795673
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB CovidRetrieval
+      type: C-MTEB/CovidRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 63.251000000000005
+    - type: map_at_10
+      value: 72.442
+    - type: map_at_100
+      value: 72.79299999999999
+    - type: map_at_1000
+      value: 72.80499999999999
+    - type: map_at_3
+      value: 70.293
+    - type: map_at_5
+      value: 71.571
+    - type: mrr_at_1
+      value: 63.541000000000004
+    - type: mrr_at_10
+      value: 72.502
+    - type: mrr_at_100
+      value: 72.846
+    - type: mrr_at_1000
+      value: 72.858
+    - type: mrr_at_3
+      value: 70.39
+    - type: mrr_at_5
+      value: 71.654
+    - type: ndcg_at_1
+      value: 63.541000000000004
+    - type: ndcg_at_10
+      value: 76.774
+    - type: ndcg_at_100
+      value: 78.389
+    - type: ndcg_at_1000
+      value: 78.678
+    - type: ndcg_at_3
+      value: 72.47
+    - type: ndcg_at_5
+      value: 74.748
+    - type: precision_at_1
+      value: 63.541000000000004
+    - type: precision_at_10
+      value: 9.115
+    - type: precision_at_100
+      value: 0.9860000000000001
+    - type: precision_at_1000
+      value: 0.101
+    - type: precision_at_3
+      value: 26.379
+    - type: precision_at_5
+      value: 16.965
+    - type: recall_at_1
+      value: 63.251000000000005
+    - type: recall_at_10
+      value: 90.253
+    - type: recall_at_100
+      value: 97.576
+    - type: recall_at_1000
+      value: 99.789
+    - type: recall_at_3
+      value: 78.635
+    - type: recall_at_5
+      value: 84.141
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB DuRetrieval
+      type: C-MTEB/DuRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 23.597
+    - type: map_at_10
+      value: 72.411
+    - type: map_at_100
+      value: 75.58500000000001
+    - type: map_at_1000
+      value: 75.64800000000001
+    - type: map_at_3
+      value: 49.61
+    - type: map_at_5
+      value: 62.527
+    - type: mrr_at_1
+      value: 84.65
+    - type: mrr_at_10
+      value: 89.43900000000001
+    - type: mrr_at_100
+      value: 89.525
+    - type: mrr_at_1000
+      value: 89.529
+    - type: mrr_at_3
+      value: 89
+    - type: mrr_at_5
+      value: 89.297
+    - type: ndcg_at_1
+      value: 84.65
+    - type: ndcg_at_10
+      value: 81.47
+    - type: ndcg_at_100
+      value: 85.198
+    - type: ndcg_at_1000
+      value: 85.828
+    - type: ndcg_at_3
+      value: 79.809
+    - type: ndcg_at_5
+      value: 78.55
+    - type: precision_at_1
+      value: 84.65
+    - type: precision_at_10
+      value: 39.595
+    - type: precision_at_100
+      value: 4.707
+    - type: precision_at_1000
+      value: 0.485
+    - type: precision_at_3
+      value: 71.61699999999999
+    - type: precision_at_5
+      value: 60.45
+    - type: recall_at_1
+      value: 23.597
+    - type: recall_at_10
+      value: 83.34
+    - type: recall_at_100
+      value: 95.19800000000001
+    - type: recall_at_1000
+      value: 98.509
+    - type: recall_at_3
+      value: 52.744
+    - type: recall_at_5
+      value: 68.411
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB EcomRetrieval
+      type: C-MTEB/EcomRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 53.1
+    - type: map_at_10
+      value: 63.359
+    - type: map_at_100
+      value: 63.9
+    - type: map_at_1000
+      value: 63.909000000000006
+    - type: map_at_3
+      value: 60.95
+    - type: map_at_5
+      value: 62.305
+    - type: mrr_at_1
+      value: 53.1
+    - type: mrr_at_10
+      value: 63.359
+    - type: mrr_at_100
+      value: 63.9
+    - type: mrr_at_1000
+      value: 63.909000000000006
+    - type: mrr_at_3
+      value: 60.95
+    - type: mrr_at_5
+      value: 62.305
+    - type: ndcg_at_1
+      value: 53.1
+    - type: ndcg_at_10
+      value: 68.418
+    - type: ndcg_at_100
+      value: 70.88499999999999
+    - type: ndcg_at_1000
+      value: 71.135
+    - type: ndcg_at_3
+      value: 63.50599999999999
+    - type: ndcg_at_5
+      value: 65.92
+    - type: precision_at_1
+      value: 53.1
+    - type: precision_at_10
+      value: 8.43
+    - type: precision_at_100
+      value: 0.955
+    - type: precision_at_1000
+      value: 0.098
+    - type: precision_at_3
+      value: 23.633000000000003
+    - type: precision_at_5
+      value: 15.340000000000002
+    - type: recall_at_1
+      value: 53.1
+    - type: recall_at_10
+      value: 84.3
+    - type: recall_at_100
+      value: 95.5
+    - type: recall_at_1000
+      value: 97.5
+    - type: recall_at_3
+      value: 70.89999999999999
+    - type: recall_at_5
+      value: 76.7
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB IFlyTek
+      type: C-MTEB/IFlyTek-classification
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 48.303193535975375
+    - type: f1
+      value: 35.96559358693866
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB JDReview
+      type: C-MTEB/JDReview-classification
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 85.06566604127579
+    - type: ap
+      value: 52.0596483757231
+    - type: f1
+      value: 79.5196835127668
+  - task:
+      type: STS
+    dataset:
+      name: MTEB LCQMC
+      type: C-MTEB/LCQMC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 74.48499423626059
+    - type: cos_sim_spearman
+      value: 78.75806756061169
+    - type: euclidean_pearson
+      value: 78.47917601852879
+    - type: euclidean_spearman
+      value: 78.75807199272622
+    - type: manhattan_pearson
+      value: 78.40207586289772
+    - type: manhattan_spearman
+      value: 78.6911776964119
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB MMarcoReranking
+      type: C-MTEB/Mmarco-reranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 24.75987466552363
+    - type: mrr
+      value: 23.40515873015873
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MMarcoRetrieval
+      type: C-MTEB/MMarcoRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 58.026999999999994
+    - type: map_at_10
+      value: 67.50699999999999
+    - type: map_at_100
+      value: 67.946
+    - type: map_at_1000
+      value: 67.96600000000001
+    - type: map_at_3
+      value: 65.503
+    - type: map_at_5
+      value: 66.649
+    - type: mrr_at_1
+      value: 60.20100000000001
+    - type: mrr_at_10
+      value: 68.271
+    - type: mrr_at_100
+      value: 68.664
+    - type: mrr_at_1000
+      value: 68.682
+    - type: mrr_at_3
+      value: 66.47800000000001
+    - type: mrr_at_5
+      value: 67.499
+    - type: ndcg_at_1
+      value: 60.20100000000001
+    - type: ndcg_at_10
+      value: 71.697
+    - type: ndcg_at_100
+      value: 73.736
+    - type: ndcg_at_1000
+      value: 74.259
+    - type: ndcg_at_3
+      value: 67.768
+    - type: ndcg_at_5
+      value: 69.72
+    - type: precision_at_1
+      value: 60.20100000000001
+    - type: precision_at_10
+      value: 8.927999999999999
+    - type: precision_at_100
+      value: 0.9950000000000001
+    - type: precision_at_1000
+      value: 0.104
+    - type: precision_at_3
+      value: 25.883
+    - type: precision_at_5
+      value: 16.55
+    - type: recall_at_1
+      value: 58.026999999999994
+    - type: recall_at_10
+      value: 83.966
+    - type: recall_at_100
+      value: 93.313
+    - type: recall_at_1000
+      value: 97.426
+    - type: recall_at_3
+      value: 73.342
+    - type: recall_at_5
+      value: 77.997
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveIntentClassification (zh-CN)
+      type: mteb/amazon_massive_intent
+      config: zh-CN
+      split: test
+      revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7
+    metrics:
+    - type: accuracy
+      value: 71.1600537995965
+    - type: f1
+      value: 68.8126216609964
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MassiveScenarioClassification (zh-CN)
+      type: mteb/amazon_massive_scenario
+      config: zh-CN
+      split: test
+      revision: 7d571f92784cd94a019292a1f45445077d0ef634
+    metrics:
+    - type: accuracy
+      value: 73.54068594485541
+    - type: f1
+      value: 73.46845879869848
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB MedicalRetrieval
+      type: C-MTEB/MedicalRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 54.900000000000006
+    - type: map_at_10
+      value: 61.363
+    - type: map_at_100
+      value: 61.924
+    - type: map_at_1000
+      value: 61.967000000000006
+    - type: map_at_3
+      value: 59.767
+    - type: map_at_5
+      value: 60.802
+    - type: mrr_at_1
+      value: 55.1
+    - type: mrr_at_10
+      value: 61.454
+    - type: mrr_at_100
+      value: 62.016000000000005
+    - type: mrr_at_1000
+      value: 62.059
+    - type: mrr_at_3
+      value: 59.882999999999996
+    - type: mrr_at_5
+      value: 60.893
+    - type: ndcg_at_1
+      value: 54.900000000000006
+    - type: ndcg_at_10
+      value: 64.423
+    - type: ndcg_at_100
+      value: 67.35900000000001
+    - type: ndcg_at_1000
+      value: 68.512
+    - type: ndcg_at_3
+      value: 61.224000000000004
+    - type: ndcg_at_5
+      value: 63.083
+    - type: precision_at_1
+      value: 54.900000000000006
+    - type: precision_at_10
+      value: 7.3999999999999995
+    - type: precision_at_100
+      value: 0.882
+    - type: precision_at_1000
+      value: 0.097
+    - type: precision_at_3
+      value: 21.8
+    - type: precision_at_5
+      value: 13.98
+    - type: recall_at_1
+      value: 54.900000000000006
+    - type: recall_at_10
+      value: 74
+    - type: recall_at_100
+      value: 88.2
+    - type: recall_at_1000
+      value: 97.3
+    - type: recall_at_3
+      value: 65.4
+    - type: recall_at_5
+      value: 69.89999999999999
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB MultilingualSentiment
+      type: C-MTEB/MultilingualSentiment-classification
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 75.15666666666667
+    - type: f1
+      value: 74.8306375354435
+  - task:
+      type: PairClassification
+    dataset:
+      name: MTEB Ocnli
+      type: C-MTEB/OCNLI
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: cos_sim_accuracy
+      value: 83.10774228478614
+    - type: cos_sim_ap
+      value: 87.17679348388666
+    - type: cos_sim_f1
+      value: 84.59302325581395
+    - type: cos_sim_precision
+      value: 78.15577439570276
+    - type: cos_sim_recall
+      value: 92.18585005279832
+    - type: dot_accuracy
+      value: 83.10774228478614
+    - type: dot_ap
+      value: 87.17679348388666
+    - type: dot_f1
+      value: 84.59302325581395
+    - type: dot_precision
+      value: 78.15577439570276
+    - type: dot_recall
+      value: 92.18585005279832
+    - type: euclidean_accuracy
+      value: 83.10774228478614
+    - type: euclidean_ap
+      value: 87.17679348388666
+    - type: euclidean_f1
+      value: 84.59302325581395
+    - type: euclidean_precision
+      value: 78.15577439570276
+    - type: euclidean_recall
+      value: 92.18585005279832
+    - type: manhattan_accuracy
+      value: 82.67460747157553
+    - type: manhattan_ap
+      value: 86.94296334435238
+    - type: manhattan_f1
+      value: 84.32327166504382
+    - type: manhattan_precision
+      value: 78.22944896115628
+    - type: manhattan_recall
+      value: 91.4466737064414
+    - type: max_accuracy
+      value: 83.10774228478614
+    - type: max_ap
+      value: 87.17679348388666
+    - type: max_f1
+      value: 84.59302325581395
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB OnlineShopping
+      type: C-MTEB/OnlineShopping-classification
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 93.24999999999999
+    - type: ap
+      value: 90.98617641063584
+    - type: f1
+      value: 93.23447883650289
+  - task:
+      type: STS
+    dataset:
+      name: MTEB PAWSX
+      type: C-MTEB/PAWSX
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 41.071417937737856
+    - type: cos_sim_spearman
+      value: 45.049199344455424
+    - type: euclidean_pearson
+      value: 44.913450096830786
+    - type: euclidean_spearman
+      value: 45.05733424275291
+    - type: manhattan_pearson
+      value: 44.881623825912065
+    - type: manhattan_spearman
+      value: 44.989923561416596
+  - task:
+      type: STS
+    dataset:
+      name: MTEB QBQTC
+      type: C-MTEB/QBQTC
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 41.38238052689359
+    - type: cos_sim_spearman
+      value: 42.61949690594399
+    - type: euclidean_pearson
+      value: 40.61261500356766
+    - type: euclidean_spearman
+      value: 42.619626605620724
+    - type: manhattan_pearson
+      value: 40.8886109204474
+    - type: manhattan_spearman
+      value: 42.75791523010463
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STS22 (zh)
+      type: mteb/sts22-crosslingual-sts
+      config: zh
+      split: test
+      revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80
+    metrics:
+    - type: cos_sim_pearson
+      value: 62.10977863727196
+    - type: cos_sim_spearman
+      value: 63.843727112473225
+    - type: euclidean_pearson
+      value: 63.25133487817196
+    - type: euclidean_spearman
+      value: 63.843727112473225
+    - type: manhattan_pearson
+      value: 63.58749018644103
+    - type: manhattan_spearman
+      value: 63.83820575456674
+  - task:
+      type: STS
+    dataset:
+      name: MTEB STSB
+      type: C-MTEB/STSB
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: cos_sim_pearson
+      value: 79.30616496720054
+    - type: cos_sim_spearman
+      value: 80.767935782436
+    - type: euclidean_pearson
+      value: 80.4160642670106
+    - type: euclidean_spearman
+      value: 80.76820284024356
+    - type: manhattan_pearson
+      value: 80.27318714580251
+    - type: manhattan_spearman
+      value: 80.61030164164964
+  - task:
+      type: Reranking
+    dataset:
+      name: MTEB T2Reranking
+      type: C-MTEB/T2Reranking
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map
+      value: 66.26242871142425
+    - type: mrr
+      value: 76.20689863623174
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB T2Retrieval
+      type: C-MTEB/T2Retrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 26.240999999999996
+    - type: map_at_10
+      value: 73.009
+    - type: map_at_100
+      value: 76.893
+    - type: map_at_1000
+      value: 76.973
+    - type: map_at_3
+      value: 51.339
+    - type: map_at_5
+      value: 63.003
+    - type: mrr_at_1
+      value: 87.458
+    - type: mrr_at_10
+      value: 90.44
+    - type: mrr_at_100
+      value: 90.558
+    - type: mrr_at_1000
+      value: 90.562
+    - type: mrr_at_3
+      value: 89.89
+    - type: mrr_at_5
+      value: 90.231
+    - type: ndcg_at_1
+      value: 87.458
+    - type: ndcg_at_10
+      value: 81.325
+    - type: ndcg_at_100
+      value: 85.61999999999999
+    - type: ndcg_at_1000
+      value: 86.394
+    - type: ndcg_at_3
+      value: 82.796
+    - type: ndcg_at_5
+      value: 81.219
+    - type: precision_at_1
+      value: 87.458
+    - type: precision_at_10
+      value: 40.534
+    - type: precision_at_100
+      value: 4.96
+    - type: precision_at_1000
+      value: 0.514
+    - type: precision_at_3
+      value: 72.444
+    - type: precision_at_5
+      value: 60.601000000000006
+    - type: recall_at_1
+      value: 26.240999999999996
+    - type: recall_at_10
+      value: 80.42
+    - type: recall_at_100
+      value: 94.118
+    - type: recall_at_1000
+      value: 98.02199999999999
+    - type: recall_at_3
+      value: 53.174
+    - type: recall_at_5
+      value: 66.739
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB TNews
+      type: C-MTEB/TNews-classification
+      config: default
+      split: validation
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 52.40899999999999
+    - type: f1
+      value: 50.68532128056062
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ThuNewsClusteringP2P
+      type: C-MTEB/ThuNewsClusteringP2P
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 65.57616085176686
+  - task:
+      type: Clustering
+    dataset:
+      name: MTEB ThuNewsClusteringS2S
+      type: C-MTEB/ThuNewsClusteringS2S
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: v_measure
+      value: 58.844999922904925
+  - task:
+      type: Retrieval
+    dataset:
+      name: MTEB VideoRetrieval
+      type: C-MTEB/VideoRetrieval
+      config: default
+      split: dev
+      revision: None
+    metrics:
+    - type: map_at_1
+      value: 58.4
+    - type: map_at_10
+      value: 68.64
+    - type: map_at_100
+      value: 69.062
+    - type: map_at_1000
+      value: 69.073
+    - type: map_at_3
+      value: 66.567
+    - type: map_at_5
+      value: 67.89699999999999
+    - type: mrr_at_1
+      value: 58.4
+    - type: mrr_at_10
+      value: 68.64
+    - type: mrr_at_100
+      value: 69.062
+    - type: mrr_at_1000
+      value: 69.073
+    - type: mrr_at_3
+      value: 66.567
+    - type: mrr_at_5
+      value: 67.89699999999999
+    - type: ndcg_at_1
+      value: 58.4
+    - type: ndcg_at_10
+      value: 73.30600000000001
+    - type: ndcg_at_100
+      value: 75.276
+    - type: ndcg_at_1000
+      value: 75.553
+    - type: ndcg_at_3
+      value: 69.126
+    - type: ndcg_at_5
+      value: 71.519
+    - type: precision_at_1
+      value: 58.4
+    - type: precision_at_10
+      value: 8.780000000000001
+    - type: precision_at_100
+      value: 0.968
+    - type: precision_at_1000
+      value: 0.099
+    - type: precision_at_3
+      value: 25.5
+    - type: precision_at_5
+      value: 16.46
+    - type: recall_at_1
+      value: 58.4
+    - type: recall_at_10
+      value: 87.8
+    - type: recall_at_100
+      value: 96.8
+    - type: recall_at_1000
+      value: 99
+    - type: recall_at_3
+      value: 76.5
+    - type: recall_at_5
+      value: 82.3
+  - task:
+      type: Classification
+    dataset:
+      name: MTEB Waimai
+      type: C-MTEB/waimai-classification
+      config: default
+      split: test
+      revision: None
+    metrics:
+    - type: accuracy
+      value: 86.21000000000001
+    - type: ap
+      value: 69.17460264576461
+    - type: f1
+      value: 84.68032984659226
+---
+
+# annofung/Dmeta-embedding-zh-Q5_K_M-GGUF
+This model was converted to GGUF format from [`DMetaSoul/Dmeta-embedding-zh`](https://huggingface.co/DMetaSoul/Dmeta-embedding-zh) 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/DMetaSoul/Dmeta-embedding-zh) for more details on the model.
+
+## Use with llama.cpp
+Install llama.cpp through brew (works on Mac and Linux)
+
+```bash
+brew install llama.cpp
+
+```
+Invoke the llama.cpp server or the CLI.
+
+### CLI:
+```bash
+llama-cli --hf-repo annofung/Dmeta-embedding-zh-Q5_K_M-GGUF --hf-file dmeta-embedding-zh-q5_k_m.gguf -p "The meaning to life and the universe is"
+```
+
+### Server:
+```bash
+llama-server --hf-repo annofung/Dmeta-embedding-zh-Q5_K_M-GGUF --hf-file dmeta-embedding-zh-q5_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.
+```
+./llama-cli --hf-repo annofung/Dmeta-embedding-zh-Q5_K_M-GGUF --hf-file dmeta-embedding-zh-q5_k_m.gguf -p "The meaning to life and the universe is"
+```
+or 
+```
+./llama-server --hf-repo annofung/Dmeta-embedding-zh-Q5_K_M-GGUF --hf-file dmeta-embedding-zh-q5_k_m.gguf -c 2048
+```