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  1. README.md +56 -294
README.md CHANGED
@@ -10,7 +10,7 @@ tags:
10
  - mteb
11
  - mteb
12
  model-index:
13
- - name: bilingual-embedding-base
14
  results:
15
  - task:
16
  type: Clustering
@@ -19,7 +19,7 @@ model-index:
19
  name: MTEB AlloProfClusteringP2P
20
  config: default
21
  split: test
22
- revision: '392ba3f5bcc8c51f578786c1fc3dae648662cb9b'
23
  metrics:
24
  - type: v_measure
25
  value: 56.88600728743999
@@ -32,7 +32,7 @@ model-index:
32
  name: MTEB AlloProfClusteringS2S
33
  config: default
34
  split: test
35
- revision: '392ba3f5bcc8c51f578786c1fc3dae648662cb9b'
36
  metrics:
37
  - type: v_measure
38
  value: 38.199527329051804
@@ -45,7 +45,7 @@ model-index:
45
  name: MTEB AlloprofReranking
46
  config: default
47
  split: test
48
- revision: '65393d0d7a08a10b4e348135e824f385d420b0fd'
49
  metrics:
50
  - type: map
51
  value: 68.73372257500206
@@ -66,7 +66,7 @@ model-index:
66
  name: MTEB AlloprofRetrieval
67
  config: default
68
  split: test
69
- revision: 'fcf295ea64c750f41fadbaa37b9b861558e1bfbd'
70
  metrics:
71
  - type: map_at_1
72
  value: 21.675
@@ -282,10 +282,10 @@ model-index:
282
  type: Classification
283
  dataset:
284
  type: mteb/amazon_reviews_multi
285
- name: MTEB AmazonReviewsClassification
286
- config: default
287
  split: test
288
- revision: '1399c76144fd37290681b995c656ef9b2e06e26d'
289
  metrics:
290
  - type: accuracy
291
  value: 43.51
@@ -300,7 +300,7 @@ model-index:
300
  name: MTEB BSARDRetrieval
301
  config: default
302
  split: test
303
- revision: '5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59'
304
  metrics:
305
  - type: map_at_1
306
  value: 5.405
@@ -519,7 +519,7 @@ model-index:
519
  name: MTEB HALClusteringS2S
520
  config: default
521
  split: test
522
- revision: 'e06ebbbb123f8144bef1a5d18796f3dec9ae2915'
523
  metrics:
524
  - type: v_measure
525
  value: 24.495384349905265
@@ -532,7 +532,7 @@ model-index:
532
  name: MTEB MLSUMClusteringP2P
533
  config: default
534
  split: test
535
- revision: 'b5d54f8f3b61ae17845046286940f03c6bc79bc7'
536
  metrics:
537
  - type: v_measure
538
  value: 41.7878688793447
@@ -545,7 +545,7 @@ model-index:
545
  name: MTEB MLSUMClusteringS2S
546
  config: default
547
  split: test
548
- revision: 'b5d54f8f3b61ae17845046286940f03c6bc79bc7'
549
  metrics:
550
  - type: v_measure
551
  value: 41.54533473611554
@@ -555,10 +555,10 @@ model-index:
555
  type: Classification
556
  dataset:
557
  type: mteb/mtop_domain
558
- name: MTEB MTOPDomainClassification
559
- config: default
560
  split: test
561
- revision: 'd80d48c1eb48d3562165c59d59d0034df9fff0bf'
562
  metrics:
563
  - type: accuracy
564
  value: 85.33041027247104
@@ -570,10 +570,10 @@ model-index:
570
  type: Classification
571
  dataset:
572
  type: mteb/mtop_intent
573
- name: MTEB MTOPIntentClassification
574
- config: default
575
  split: test
576
- revision: 'ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba'
577
  metrics:
578
  - type: accuracy
579
  value: 59.01346695897275
@@ -585,10 +585,10 @@ model-index:
585
  type: Classification
586
  dataset:
587
  type: mteb/masakhanews
588
- name: MTEB MasakhaNEWSClassification
589
- config: default
590
  split: test
591
- revision: '18193f187b92da67168c655c9973a165ed9593dd'
592
  metrics:
593
  - type: accuracy
594
  value: 72.60663507109004
@@ -600,10 +600,10 @@ model-index:
600
  type: Clustering
601
  dataset:
602
  type: masakhane/masakhanews
603
- name: MTEB MasakhaNEWSClusteringP2P
604
- config: default
605
  split: test
606
- revision: '8ccc72e69e65f40c70e117d8b3c08306bb788b60'
607
  metrics:
608
  - type: v_measure
609
  value: 49.17691007381563
@@ -613,10 +613,10 @@ model-index:
613
  type: Clustering
614
  dataset:
615
  type: masakhane/masakhanews
616
- name: MTEB MasakhaNEWSClusteringS2S
617
- config: default
618
  split: test
619
- revision: '8ccc72e69e65f40c70e117d8b3c08306bb788b60'
620
  metrics:
621
  - type: v_measure
622
  value: 26.9350763881635
@@ -626,10 +626,10 @@ model-index:
626
  type: Classification
627
  dataset:
628
  type: mteb/amazon_massive_intent
629
- name: MTEB MassiveIntentClassification
630
- config: default
631
  split: test
632
- revision: '4672e20407010da34463acc759c162ca9734bca6'
633
  metrics:
634
  - type: accuracy
635
  value: 65.1546738399462
@@ -641,10 +641,10 @@ model-index:
641
  type: Classification
642
  dataset:
643
  type: mteb/amazon_massive_scenario
644
- name: MTEB MassiveScenarioClassification
645
- config: default
646
  split: test
647
- revision: 'fad2c6e8459f9e1c45d9315f4953d921437d70f8'
648
  metrics:
649
  - type: accuracy
650
  value: 69.94283792871553
@@ -656,10 +656,10 @@ model-index:
656
  type: Retrieval
657
  dataset:
658
  type: jinaai/mintakaqa
659
- name: MTEB MintakaRetrieval
660
- config: default
661
  split: test
662
- revision: 'efa78cc2f74bbcd21eff2261f9e13aebe40b814e'
663
  metrics:
664
  - type: map_at_1
665
  value: 14.536999999999999
@@ -875,10 +875,10 @@ model-index:
875
  type: PairClassification
876
  dataset:
877
  type: GEM/opusparcus
878
- name: MTEB OpusparcusPC
879
- config: default
880
  split: test
881
- revision: '9e9b1f8ef51616073f47f306f7f47dd91663f86a'
882
  metrics:
883
  - type: cos_sim_accuracy
884
  value: 81.74386920980926
@@ -930,10 +930,10 @@ model-index:
930
  type: PairClassification
931
  dataset:
932
  type: google-research-datasets/paws-x
933
- name: MTEB PawsX
934
- config: default
935
  split: test
936
- revision: '8a04d940a42cd40658986fdd8e3da561533a3646'
937
  metrics:
938
  - type: cos_sim_accuracy
939
  value: 61.1
@@ -988,7 +988,7 @@ model-index:
988
  name: MTEB SICKFr
989
  config: default
990
  split: test
991
- revision: 'e077ab4cf4774a1e36d86d593b150422fafd8e8a'
992
  metrics:
993
  - type: cos_sim_pearson
994
  value: 83.1543597030015
@@ -1006,10 +1006,10 @@ model-index:
1006
  type: STS
1007
  dataset:
1008
  type: mteb/sts22-crosslingual-sts
1009
- name: MTEB STS22
1010
- config: default
1011
  split: test
1012
- revision: 'de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3'
1013
  metrics:
1014
  - type: cos_sim_pearson
1015
  value: 79.20797144286122
@@ -1026,11 +1026,11 @@ model-index:
1026
  - task:
1027
  type: STS
1028
  dataset:
1029
- type: mteb/stsb_multi_mt
1030
- name: MTEB STSBenchmarkMultilingualSTS
1031
- config: default
1032
  split: test
1033
- revision: '29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c'
1034
  metrics:
1035
  - type: cos_sim_pearson
1036
  value: 84.69215133897265
@@ -1051,7 +1051,7 @@ model-index:
1051
  name: MTEB SummEvalFr
1052
  config: default
1053
  split: test
1054
- revision: 'b385812de6a9577b6f4d0f88c6a6e35395a94054'
1055
  metrics:
1056
  - type: cos_sim_pearson
1057
  value: 29.187176809104393
@@ -1068,7 +1068,7 @@ model-index:
1068
  name: MTEB SyntecReranking
1069
  config: default
1070
  split: test
1071
- revision: 'daf0863838cd9e3ba50544cdce3ac2b338a1b0ad'
1072
  metrics:
1073
  - type: map
1074
  value: 82.76666666666667
@@ -1089,7 +1089,7 @@ model-index:
1089
  name: MTEB SyntecRetrieval
1090
  config: default
1091
  split: test
1092
- revision: '19661ccdca4dfc2d15122d776b61685f48c68ca9'
1093
  metrics:
1094
  - type: map_at_1
1095
  value: 57.99999999999999
@@ -1305,10 +1305,10 @@ model-index:
1305
  type: Retrieval
1306
  dataset:
1307
  type: jinaai/xpqa
1308
- name: MTEB XPQARetrieval
1309
- config: default
1310
  split: test
1311
- revision: 'c99d599f0a6ab9b85b065da6f9d94f9cf731679f'
1312
  metrics:
1313
  - type: map_at_1
1314
  value: 35.256
@@ -1520,244 +1520,6 @@ model-index:
1520
  value: 53.371
1521
  - type: recall_at_5
1522
  value: 59.399
1523
- - task:
1524
- type: Classification
1525
- dataset:
1526
- type: CustomDataset
1527
- name: MTEB MassiveIntentClassification (fr)
1528
- config: fr
1529
- split: test
1530
- revision: '1.0'
1531
- metrics:
1532
- - type: accuracy
1533
- value: 0.0
1534
- - type: precision
1535
- value: 0.0
1536
- - type: recall
1537
- value: 0.0
1538
- - type: f1
1539
- value: 0.0
1540
- - task:
1541
- type: Classification
1542
- dataset:
1543
- type: CustomDataset
1544
- name: MTEB MTOPIntentClassification (fr)
1545
- config: fr
1546
- split: test
1547
- revision: '1.0'
1548
- metrics:
1549
- - type: accuracy
1550
- value: 0.0
1551
- - type: precision
1552
- value: 0.0
1553
- - type: recall
1554
- value: 0.0
1555
- - type: f1
1556
- value: 0.0
1557
- - task:
1558
- type: Classification
1559
- dataset:
1560
- type: CustomDataset
1561
- name: MTEB MintakaRetrieval (fr)
1562
- config: fr
1563
- split: test
1564
- revision: '1.0'
1565
- metrics:
1566
- - type: accuracy
1567
- value: 0.0
1568
- - type: precision
1569
- value: 0.0
1570
- - type: recall
1571
- value: 0.0
1572
- - type: f1
1573
- value: 0.0
1574
- - task:
1575
- type: Classification
1576
- dataset:
1577
- type: CustomDataset
1578
- name: MTEB XPQARetrieval (fr)
1579
- config: fr
1580
- split: test
1581
- revision: '1.0'
1582
- metrics:
1583
- - type: accuracy
1584
- value: 0.0
1585
- - type: precision
1586
- value: 0.0
1587
- - type: recall
1588
- value: 0.0
1589
- - type: f1
1590
- value: 0.0
1591
- - task:
1592
- type: Classification
1593
- dataset:
1594
- type: CustomDataset
1595
- name: MTEB OpusparcusPC (fr)
1596
- config: fr
1597
- split: test
1598
- revision: '1.0'
1599
- metrics:
1600
- - type: accuracy
1601
- value: 0.0
1602
- - type: precision
1603
- value: 0.0
1604
- - type: recall
1605
- value: 0.0
1606
- - type: f1
1607
- value: 0.0
1608
- - task:
1609
- type: Classification
1610
- dataset:
1611
- type: CustomDataset
1612
- name: MTEB MTOPDomainClassification (fr)
1613
- config: fr
1614
- split: test
1615
- revision: '1.0'
1616
- metrics:
1617
- - type: accuracy
1618
- value: 0.0
1619
- - type: precision
1620
- value: 0.0
1621
- - type: recall
1622
- value: 0.0
1623
- - type: f1
1624
- value: 0.0
1625
- - task:
1626
- type: Classification
1627
- dataset:
1628
- type: CustomDataset
1629
- name: MTEB AmazonReviewsClassification (fr)
1630
- config: fr
1631
- split: test
1632
- revision: '1.0'
1633
- metrics:
1634
- - type: accuracy
1635
- value: 0.0
1636
- - type: precision
1637
- value: 0.0
1638
- - type: recall
1639
- value: 0.0
1640
- - type: f1
1641
- value: 0.0
1642
- - task:
1643
- type: Classification
1644
- dataset:
1645
- type: CustomDataset
1646
- name: MTEB STS22 (fr)
1647
- config: fr
1648
- split: test
1649
- revision: '1.0'
1650
- metrics:
1651
- - type: accuracy
1652
- value: 0.0
1653
- - type: precision
1654
- value: 0.0
1655
- - type: recall
1656
- value: 0.0
1657
- - type: f1
1658
- value: 0.0
1659
- - task:
1660
- type: Classification
1661
- dataset:
1662
- type: CustomDataset
1663
- name: MTEB STSBenchmarkMultilingualSTS (fr)
1664
- config: fr
1665
- split: test
1666
- revision: '1.0'
1667
- metrics:
1668
- - type: accuracy
1669
- value: 0.0
1670
- - type: precision
1671
- value: 0.0
1672
- - type: recall
1673
- value: 0.0
1674
- - type: f1
1675
- value: 0.0
1676
- - task:
1677
- type: Classification
1678
- dataset:
1679
- type: CustomDataset
1680
- name: MTEB PawsX (fr)
1681
- config: fr
1682
- split: test
1683
- revision: '1.0'
1684
- metrics:
1685
- - type: accuracy
1686
- value: 0.0
1687
- - type: precision
1688
- value: 0.0
1689
- - type: recall
1690
- value: 0.0
1691
- - type: f1
1692
- value: 0.0
1693
- - task:
1694
- type: Classification
1695
- dataset:
1696
- type: CustomDataset
1697
- name: MTEB MassiveScenarioClassification (fr)
1698
- config: fr
1699
- split: test
1700
- revision: '1.0'
1701
- metrics:
1702
- - type: accuracy
1703
- value: 0.0
1704
- - type: precision
1705
- value: 0.0
1706
- - type: recall
1707
- value: 0.0
1708
- - type: f1
1709
- value: 0.0
1710
- - task:
1711
- type: Classification
1712
- dataset:
1713
- type: CustomDataset
1714
- name: MTEB MasakhaNEWSClassification (fra)
1715
- config: fra
1716
- split: test
1717
- revision: '1.0'
1718
- metrics:
1719
- - type: accuracy
1720
- value: 0.0
1721
- - type: precision
1722
- value: 0.0
1723
- - type: recall
1724
- value: 0.0
1725
- - type: f1
1726
- value: 0.0
1727
- - task:
1728
- type: Classification
1729
- dataset:
1730
- type: CustomDataset
1731
- name: MTEB MasakhaNEWSClusteringS2S (fra)
1732
- config: fra
1733
- split: test
1734
- revision: '1.0'
1735
- metrics:
1736
- - type: accuracy
1737
- value: 0.0
1738
- - type: precision
1739
- value: 0.0
1740
- - type: recall
1741
- value: 0.0
1742
- - type: f1
1743
- value: 0.0
1744
- - task:
1745
- type: Classification
1746
- dataset:
1747
- type: CustomDataset
1748
- name: MTEB MasakhaNEWSClusteringP2P (fra)
1749
- config: fra
1750
- split: test
1751
- revision: '1.0'
1752
- metrics:
1753
- - type: accuracy
1754
- value: 0.0
1755
- - type: precision
1756
- value: 0.0
1757
- - type: recall
1758
- value: 0.0
1759
- - type: f1
1760
- value: 0.0
1761
  license: apache-2.0
1762
  ---
1763
 
 
10
  - mteb
11
  - mteb
12
  model-index:
13
+ - name: e433e634850d125d8b85bee76db3a3b6a0c3bf56
14
  results:
15
  - task:
16
  type: Clustering
 
19
  name: MTEB AlloProfClusteringP2P
20
  config: default
21
  split: test
22
+ revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
23
  metrics:
24
  - type: v_measure
25
  value: 56.88600728743999
 
32
  name: MTEB AlloProfClusteringS2S
33
  config: default
34
  split: test
35
+ revision: 392ba3f5bcc8c51f578786c1fc3dae648662cb9b
36
  metrics:
37
  - type: v_measure
38
  value: 38.199527329051804
 
45
  name: MTEB AlloprofReranking
46
  config: default
47
  split: test
48
+ revision: 65393d0d7a08a10b4e348135e824f385d420b0fd
49
  metrics:
50
  - type: map
51
  value: 68.73372257500206
 
66
  name: MTEB AlloprofRetrieval
67
  config: default
68
  split: test
69
+ revision: fcf295ea64c750f41fadbaa37b9b861558e1bfbd
70
  metrics:
71
  - type: map_at_1
72
  value: 21.675
 
282
  type: Classification
283
  dataset:
284
  type: mteb/amazon_reviews_multi
285
+ name: MTEB AmazonReviewsClassification (fr)
286
+ config: fr
287
  split: test
288
+ revision: 1399c76144fd37290681b995c656ef9b2e06e26d
289
  metrics:
290
  - type: accuracy
291
  value: 43.51
 
300
  name: MTEB BSARDRetrieval
301
  config: default
302
  split: test
303
+ revision: 5effa1b9b5fa3b0f9e12523e6e43e5f86a6e6d59
304
  metrics:
305
  - type: map_at_1
306
  value: 5.405
 
519
  name: MTEB HALClusteringS2S
520
  config: default
521
  split: test
522
+ revision: e06ebbbb123f8144bef1a5d18796f3dec9ae2915
523
  metrics:
524
  - type: v_measure
525
  value: 24.495384349905265
 
532
  name: MTEB MLSUMClusteringP2P
533
  config: default
534
  split: test
535
+ revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
536
  metrics:
537
  - type: v_measure
538
  value: 41.7878688793447
 
545
  name: MTEB MLSUMClusteringS2S
546
  config: default
547
  split: test
548
+ revision: b5d54f8f3b61ae17845046286940f03c6bc79bc7
549
  metrics:
550
  - type: v_measure
551
  value: 41.54533473611554
 
555
  type: Classification
556
  dataset:
557
  type: mteb/mtop_domain
558
+ name: MTEB MTOPDomainClassification (fr)
559
+ config: fr
560
  split: test
561
+ revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf
562
  metrics:
563
  - type: accuracy
564
  value: 85.33041027247104
 
570
  type: Classification
571
  dataset:
572
  type: mteb/mtop_intent
573
+ name: MTEB MTOPIntentClassification (fr)
574
+ config: fr
575
  split: test
576
+ revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba
577
  metrics:
578
  - type: accuracy
579
  value: 59.01346695897275
 
585
  type: Classification
586
  dataset:
587
  type: mteb/masakhanews
588
+ name: MTEB MasakhaNEWSClassification (fra)
589
+ config: fra
590
  split: test
591
+ revision: 18193f187b92da67168c655c9973a165ed9593dd
592
  metrics:
593
  - type: accuracy
594
  value: 72.60663507109004
 
600
  type: Clustering
601
  dataset:
602
  type: masakhane/masakhanews
603
+ name: MTEB MasakhaNEWSClusteringP2P (fra)
604
+ config: fra
605
  split: test
606
+ revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
607
  metrics:
608
  - type: v_measure
609
  value: 49.17691007381563
 
613
  type: Clustering
614
  dataset:
615
  type: masakhane/masakhanews
616
+ name: MTEB MasakhaNEWSClusteringS2S (fra)
617
+ config: fra
618
  split: test
619
+ revision: 8ccc72e69e65f40c70e117d8b3c08306bb788b60
620
  metrics:
621
  - type: v_measure
622
  value: 26.9350763881635
 
626
  type: Classification
627
  dataset:
628
  type: mteb/amazon_massive_intent
629
+ name: MTEB MassiveIntentClassification (fr)
630
+ config: fr
631
  split: test
632
+ revision: 4672e20407010da34463acc759c162ca9734bca6
633
  metrics:
634
  - type: accuracy
635
  value: 65.1546738399462
 
641
  type: Classification
642
  dataset:
643
  type: mteb/amazon_massive_scenario
644
+ name: MTEB MassiveScenarioClassification (fr)
645
+ config: fr
646
  split: test
647
+ revision: fad2c6e8459f9e1c45d9315f4953d921437d70f8
648
  metrics:
649
  - type: accuracy
650
  value: 69.94283792871553
 
656
  type: Retrieval
657
  dataset:
658
  type: jinaai/mintakaqa
659
+ name: MTEB MintakaRetrieval (fr)
660
+ config: fr
661
  split: test
662
+ revision: efa78cc2f74bbcd21eff2261f9e13aebe40b814e
663
  metrics:
664
  - type: map_at_1
665
  value: 14.536999999999999
 
875
  type: PairClassification
876
  dataset:
877
  type: GEM/opusparcus
878
+ name: MTEB OpusparcusPC (fr)
879
+ config: fr
880
  split: test
881
+ revision: 9e9b1f8ef51616073f47f306f7f47dd91663f86a
882
  metrics:
883
  - type: cos_sim_accuracy
884
  value: 81.74386920980926
 
930
  type: PairClassification
931
  dataset:
932
  type: google-research-datasets/paws-x
933
+ name: MTEB PawsX (fr)
934
+ config: fr
935
  split: test
936
+ revision: 8a04d940a42cd40658986fdd8e3da561533a3646
937
  metrics:
938
  - type: cos_sim_accuracy
939
  value: 61.1
 
988
  name: MTEB SICKFr
989
  config: default
990
  split: test
991
+ revision: e077ab4cf4774a1e36d86d593b150422fafd8e8a
992
  metrics:
993
  - type: cos_sim_pearson
994
  value: 83.1543597030015
 
1006
  type: STS
1007
  dataset:
1008
  type: mteb/sts22-crosslingual-sts
1009
+ name: MTEB STS22 (fr)
1010
+ config: fr
1011
  split: test
1012
+ revision: de9d86b3b84231dc21f76c7b7af1f28e2f57f6e3
1013
  metrics:
1014
  - type: cos_sim_pearson
1015
  value: 79.20797144286122
 
1026
  - task:
1027
  type: STS
1028
  dataset:
1029
+ type: PhilipMay/stsb_multi_mt
1030
+ name: MTEB STSBenchmarkMultilingualSTS (fr)
1031
+ config: fr
1032
  split: test
1033
+ revision: 29afa2569dcedaaa2fe6a3dcfebab33d28b82e8c
1034
  metrics:
1035
  - type: cos_sim_pearson
1036
  value: 84.69215133897265
 
1051
  name: MTEB SummEvalFr
1052
  config: default
1053
  split: test
1054
+ revision: b385812de6a9577b6f4d0f88c6a6e35395a94054
1055
  metrics:
1056
  - type: cos_sim_pearson
1057
  value: 29.187176809104393
 
1068
  name: MTEB SyntecReranking
1069
  config: default
1070
  split: test
1071
+ revision: daf0863838cd9e3ba50544cdce3ac2b338a1b0ad
1072
  metrics:
1073
  - type: map
1074
  value: 82.76666666666667
 
1089
  name: MTEB SyntecRetrieval
1090
  config: default
1091
  split: test
1092
+ revision: 19661ccdca4dfc2d15122d776b61685f48c68ca9
1093
  metrics:
1094
  - type: map_at_1
1095
  value: 57.99999999999999
 
1305
  type: Retrieval
1306
  dataset:
1307
  type: jinaai/xpqa
1308
+ name: MTEB XPQARetrieval (fr)
1309
+ config: fr
1310
  split: test
1311
+ revision: c99d599f0a6ab9b85b065da6f9d94f9cf731679f
1312
  metrics:
1313
  - type: map_at_1
1314
  value: 35.256
 
1520
  value: 53.371
1521
  - type: recall_at_5
1522
  value: 59.399
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1523
  license: apache-2.0
1524
  ---
1525