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--- |
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tags: |
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- mteb |
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model-index: |
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- name: bge-small-en-v1.5-quant |
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results: |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_counterfactual |
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name: MTEB AmazonCounterfactualClassification (en) |
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config: en |
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split: test |
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revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
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metrics: |
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- type: accuracy |
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value: 74.19402985074626 |
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- type: ap |
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value: 37.562368912364036 |
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- type: f1 |
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value: 68.47046663470138 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_polarity |
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name: MTEB AmazonPolarityClassification |
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config: default |
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split: test |
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revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
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metrics: |
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- type: accuracy |
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value: 91.89432499999998 |
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- type: ap |
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value: 88.64572979375352 |
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- type: f1 |
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value: 91.87171177424113 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_reviews_multi |
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name: MTEB AmazonReviewsClassification (en) |
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config: en |
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split: test |
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revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
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metrics: |
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- type: accuracy |
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value: 46.71799999999999 |
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- type: f1 |
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value: 46.25791412217894 |
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- task: |
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type: Retrieval |
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dataset: |
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type: arguana |
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name: MTEB ArguAna |
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config: default |
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split: test |
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revision: None |
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metrics: |
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- type: map_at_1 |
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value: 34.424 |
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- type: map_at_10 |
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value: 49.63 |
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- type: map_at_100 |
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value: 50.477000000000004 |
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- type: map_at_1000 |
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value: 50.483 |
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- type: map_at_3 |
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value: 45.389 |
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- type: map_at_5 |
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value: 47.888999999999996 |
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- type: mrr_at_1 |
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value: 34.78 |
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- type: mrr_at_10 |
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value: 49.793 |
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- type: mrr_at_100 |
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value: 50.632999999999996 |
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- type: mrr_at_1000 |
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value: 50.638000000000005 |
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- type: mrr_at_3 |
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value: 45.531 |
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- type: mrr_at_5 |
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value: 48.010000000000005 |
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- type: ndcg_at_1 |
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value: 34.424 |
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- type: ndcg_at_10 |
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value: 57.774 |
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- type: ndcg_at_100 |
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value: 61.248000000000005 |
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- type: ndcg_at_1000 |
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value: 61.378 |
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- type: ndcg_at_3 |
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value: 49.067 |
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- type: ndcg_at_5 |
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value: 53.561 |
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- type: precision_at_1 |
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value: 34.424 |
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- type: precision_at_10 |
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value: 8.364 |
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- type: precision_at_100 |
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value: 0.985 |
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- type: precision_at_1000 |
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value: 0.1 |
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- type: precision_at_3 |
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value: 19.915 |
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- type: precision_at_5 |
|
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value: 14.124999999999998 |
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- type: recall_at_1 |
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value: 34.424 |
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- type: recall_at_10 |
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value: 83.64200000000001 |
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- type: recall_at_100 |
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value: 98.506 |
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- type: recall_at_1000 |
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value: 99.502 |
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- type: recall_at_3 |
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value: 59.744 |
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- type: recall_at_5 |
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value: 70.626 |
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- task: |
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type: Reranking |
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dataset: |
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type: mteb/askubuntudupquestions-reranking |
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name: MTEB AskUbuntuDupQuestions |
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config: default |
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split: test |
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revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
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metrics: |
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- type: map |
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value: 62.40334669601722 |
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- type: mrr |
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value: 75.33175042870333 |
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- task: |
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type: STS |
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dataset: |
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type: mteb/biosses-sts |
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name: MTEB BIOSSES |
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config: default |
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split: test |
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revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
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metrics: |
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- type: cos_sim_pearson |
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value: 88.00433892980047 |
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- type: cos_sim_spearman |
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value: 86.65558896421105 |
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- type: euclidean_pearson |
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value: 85.98927300398377 |
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- type: euclidean_spearman |
|
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value: 86.0905158476729 |
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- type: manhattan_pearson |
|
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value: 86.0272425017433 |
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- type: manhattan_spearman |
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value: 85.8929209838941 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/banking77 |
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name: MTEB Banking77Classification |
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config: default |
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split: test |
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revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
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metrics: |
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- type: accuracy |
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value: 85.1038961038961 |
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- type: f1 |
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value: 85.06851570045757 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/emotion |
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name: MTEB EmotionClassification |
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config: default |
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split: test |
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revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
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metrics: |
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- type: accuracy |
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value: 46.845 |
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- type: f1 |
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value: 41.70045120106269 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/imdb |
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name: MTEB ImdbClassification |
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config: default |
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split: test |
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revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
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metrics: |
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- type: accuracy |
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value: 89.3476 |
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- type: ap |
|
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value: 85.26891728027032 |
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- type: f1 |
|
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value: 89.33488973832894 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/mtop_domain |
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name: MTEB MTOPDomainClassification (en) |
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config: en |
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split: test |
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revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
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metrics: |
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- type: accuracy |
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value: 92.67441860465115 |
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- type: f1 |
|
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value: 92.48821366022861 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/mtop_intent |
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name: MTEB MTOPIntentClassification (en) |
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config: en |
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split: test |
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revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
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metrics: |
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|
- type: accuracy |
|
|
value: 74.02872777017784 |
|
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- type: f1 |
|
|
value: 57.28822860484337 |
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- task: |
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type: Classification |
|
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dataset: |
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type: mteb/amazon_massive_intent |
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name: MTEB MassiveIntentClassification (en) |
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config: en |
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split: test |
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revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
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metrics: |
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- type: accuracy |
|
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value: 74.01479488903833 |
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- type: f1 |
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value: 71.83716204573571 |
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- task: |
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type: Classification |
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dataset: |
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type: mteb/amazon_massive_scenario |
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name: MTEB MassiveScenarioClassification (en) |
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config: en |
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split: test |
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revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
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metrics: |
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- type: accuracy |
|
|
value: 77.95897780766644 |
|
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- type: f1 |
|
|
value: 77.80380046125542 |
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- task: |
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type: STS |
|
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dataset: |
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type: mteb/sickr-sts |
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name: MTEB SICK-R |
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config: default |
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split: test |
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revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
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metrics: |
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- type: cos_sim_pearson |
|
|
value: 83.86793477948164 |
|
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- type: cos_sim_spearman |
|
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value: 79.43675709317894 |
|
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- type: euclidean_pearson |
|
|
value: 81.42564463337872 |
|
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- type: euclidean_spearman |
|
|
value: 79.39138648510273 |
|
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- type: manhattan_pearson |
|
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value: 81.31167449689285 |
|
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- type: manhattan_spearman |
|
|
value: 79.28411420758785 |
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- task: |
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type: STS |
|
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dataset: |
|
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type: mteb/sts12-sts |
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name: MTEB STS12 |
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config: default |
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split: test |
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revision: a0d554a64d88156834ff5ae9920b964011b16384 |
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metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 84.43490408077298 |
|
|
- type: cos_sim_spearman |
|
|
value: 76.16878340109265 |
|
|
- type: euclidean_pearson |
|
|
value: 80.6016219080782 |
|
|
- type: euclidean_spearman |
|
|
value: 75.67063072565917 |
|
|
- type: manhattan_pearson |
|
|
value: 80.7238920179759 |
|
|
- type: manhattan_spearman |
|
|
value: 75.85631683403953 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts13-sts |
|
|
name: MTEB STS13 |
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|
config: default |
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|
split: test |
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revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
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|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 83.03882477767792 |
|
|
- type: cos_sim_spearman |
|
|
value: 84.15171505206217 |
|
|
- type: euclidean_pearson |
|
|
value: 84.11692506470922 |
|
|
- type: euclidean_spearman |
|
|
value: 84.78589046217311 |
|
|
- type: manhattan_pearson |
|
|
value: 83.98651139454486 |
|
|
- type: manhattan_spearman |
|
|
value: 84.64928563751276 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts14-sts |
|
|
name: MTEB STS14 |
|
|
config: default |
|
|
split: test |
|
|
revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
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|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 83.11158600428418 |
|
|
- type: cos_sim_spearman |
|
|
value: 81.48561519933875 |
|
|
- type: euclidean_pearson |
|
|
value: 83.21025907155807 |
|
|
- type: euclidean_spearman |
|
|
value: 81.68699235487654 |
|
|
- type: manhattan_pearson |
|
|
value: 83.16704771658094 |
|
|
- type: manhattan_spearman |
|
|
value: 81.7133110412898 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts15-sts |
|
|
name: MTEB STS15 |
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|
config: default |
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|
split: test |
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revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
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metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 87.1514510686502 |
|
|
- type: cos_sim_spearman |
|
|
value: 88.11449450494452 |
|
|
- type: euclidean_pearson |
|
|
value: 87.75854949349939 |
|
|
- type: euclidean_spearman |
|
|
value: 88.4055148221637 |
|
|
- type: manhattan_pearson |
|
|
value: 87.71487828059706 |
|
|
- type: manhattan_spearman |
|
|
value: 88.35301381116254 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts16-sts |
|
|
name: MTEB STS16 |
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|
config: default |
|
|
split: test |
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revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
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metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 83.36838640113687 |
|
|
- type: cos_sim_spearman |
|
|
value: 84.98776974283366 |
|
|
- type: euclidean_pearson |
|
|
value: 84.0617526427129 |
|
|
- type: euclidean_spearman |
|
|
value: 85.04234805662242 |
|
|
- type: manhattan_pearson |
|
|
value: 83.87433162971784 |
|
|
- type: manhattan_spearman |
|
|
value: 84.87174280390242 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts17-crosslingual-sts |
|
|
name: MTEB STS17 (en-en) |
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|
config: en-en |
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|
split: test |
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revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
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|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 87.72465270691285 |
|
|
- type: cos_sim_spearman |
|
|
value: 87.97672332532184 |
|
|
- type: euclidean_pearson |
|
|
value: 88.78764701492182 |
|
|
- type: euclidean_spearman |
|
|
value: 88.3509718074474 |
|
|
- type: manhattan_pearson |
|
|
value: 88.73024739256215 |
|
|
- type: manhattan_spearman |
|
|
value: 88.24149566970154 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/sts22-crosslingual-sts |
|
|
name: MTEB STS22 (en) |
|
|
config: en |
|
|
split: test |
|
|
revision: 6d1ba47164174a496b7fa5d3569dae26a6813b80 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 64.65195562203238 |
|
|
- type: cos_sim_spearman |
|
|
value: 65.0726777678982 |
|
|
- type: euclidean_pearson |
|
|
value: 65.84698245675273 |
|
|
- type: euclidean_spearman |
|
|
value: 65.13121502162804 |
|
|
- type: manhattan_pearson |
|
|
value: 65.96149904857049 |
|
|
- type: manhattan_spearman |
|
|
value: 65.39983948112955 |
|
|
- task: |
|
|
type: STS |
|
|
dataset: |
|
|
type: mteb/stsbenchmark-sts |
|
|
name: MTEB STSBenchmark |
|
|
config: default |
|
|
split: test |
|
|
revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
|
|
metrics: |
|
|
- type: cos_sim_pearson |
|
|
value: 85.2642818050049 |
|
|
- type: cos_sim_spearman |
|
|
value: 86.30633382439257 |
|
|
- type: euclidean_pearson |
|
|
value: 86.46510435905633 |
|
|
- type: euclidean_spearman |
|
|
value: 86.62650496446 |
|
|
- type: manhattan_pearson |
|
|
value: 86.2546330637872 |
|
|
- type: manhattan_spearman |
|
|
value: 86.46309860938591 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: mteb/sprintduplicatequestions-pairclassification |
|
|
name: MTEB SprintDuplicateQuestions |
|
|
config: default |
|
|
split: test |
|
|
revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 99.84257425742574 |
|
|
- type: cos_sim_ap |
|
|
value: 96.25445889914926 |
|
|
- type: cos_sim_f1 |
|
|
value: 92.03805708562844 |
|
|
- type: cos_sim_precision |
|
|
value: 92.1765295887663 |
|
|
- type: cos_sim_recall |
|
|
value: 91.9 |
|
|
- type: dot_accuracy |
|
|
value: 99.83069306930693 |
|
|
- type: dot_ap |
|
|
value: 96.00517778550396 |
|
|
- type: dot_f1 |
|
|
value: 91.27995920448751 |
|
|
- type: dot_precision |
|
|
value: 93.1321540062435 |
|
|
- type: dot_recall |
|
|
value: 89.5 |
|
|
- type: euclidean_accuracy |
|
|
value: 99.84455445544555 |
|
|
- type: euclidean_ap |
|
|
value: 96.14761524546034 |
|
|
- type: euclidean_f1 |
|
|
value: 91.97751660705163 |
|
|
- type: euclidean_precision |
|
|
value: 94.04388714733543 |
|
|
- type: euclidean_recall |
|
|
value: 90 |
|
|
- type: manhattan_accuracy |
|
|
value: 99.84158415841584 |
|
|
- type: manhattan_ap |
|
|
value: 96.17014673429341 |
|
|
- type: manhattan_f1 |
|
|
value: 91.93790686029043 |
|
|
- type: manhattan_precision |
|
|
value: 92.07622868605817 |
|
|
- type: manhattan_recall |
|
|
value: 91.8 |
|
|
- type: max_accuracy |
|
|
value: 99.84455445544555 |
|
|
- type: max_ap |
|
|
value: 96.25445889914926 |
|
|
- type: max_f1 |
|
|
value: 92.03805708562844 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/toxic_conversations_50k |
|
|
name: MTEB ToxicConversationsClassification |
|
|
config: default |
|
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split: test |
|
|
revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 69.5008 |
|
|
- type: ap |
|
|
value: 13.64158304183089 |
|
|
- type: f1 |
|
|
value: 53.50073331072236 |
|
|
- task: |
|
|
type: Classification |
|
|
dataset: |
|
|
type: mteb/tweet_sentiment_extraction |
|
|
name: MTEB TweetSentimentExtractionClassification |
|
|
config: default |
|
|
split: test |
|
|
revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
|
|
metrics: |
|
|
- type: accuracy |
|
|
value: 60.01980758347483 |
|
|
- type: f1 |
|
|
value: 60.35679678249753 |
|
|
- task: |
|
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type: PairClassification |
|
|
dataset: |
|
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type: mteb/twittersemeval2015-pairclassification |
|
|
name: MTEB TwitterSemEval2015 |
|
|
config: default |
|
|
split: test |
|
|
revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 85.68874053764081 |
|
|
- type: cos_sim_ap |
|
|
value: 73.26334732095694 |
|
|
- type: cos_sim_f1 |
|
|
value: 68.01558376272465 |
|
|
- type: cos_sim_precision |
|
|
value: 64.93880489560834 |
|
|
- type: cos_sim_recall |
|
|
value: 71.39841688654354 |
|
|
- type: dot_accuracy |
|
|
value: 84.71121177802945 |
|
|
- type: dot_ap |
|
|
value: 70.33606362522605 |
|
|
- type: dot_f1 |
|
|
value: 65.0887573964497 |
|
|
- type: dot_precision |
|
|
value: 63.50401606425703 |
|
|
- type: dot_recall |
|
|
value: 66.75461741424802 |
|
|
- type: euclidean_accuracy |
|
|
value: 85.80795136198367 |
|
|
- type: euclidean_ap |
|
|
value: 73.43201285001163 |
|
|
- type: euclidean_f1 |
|
|
value: 68.33166833166834 |
|
|
- type: euclidean_precision |
|
|
value: 64.86486486486487 |
|
|
- type: euclidean_recall |
|
|
value: 72.18997361477572 |
|
|
- type: manhattan_accuracy |
|
|
value: 85.62317458425225 |
|
|
- type: manhattan_ap |
|
|
value: 73.21212085536185 |
|
|
- type: manhattan_f1 |
|
|
value: 68.01681314482232 |
|
|
- type: manhattan_precision |
|
|
value: 65.74735286875153 |
|
|
- type: manhattan_recall |
|
|
value: 70.44854881266491 |
|
|
- type: max_accuracy |
|
|
value: 85.80795136198367 |
|
|
- type: max_ap |
|
|
value: 73.43201285001163 |
|
|
- type: max_f1 |
|
|
value: 68.33166833166834 |
|
|
- task: |
|
|
type: PairClassification |
|
|
dataset: |
|
|
type: mteb/twitterurlcorpus-pairclassification |
|
|
name: MTEB TwitterURLCorpus |
|
|
config: default |
|
|
split: test |
|
|
revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
|
|
metrics: |
|
|
- type: cos_sim_accuracy |
|
|
value: 88.81709162882757 |
|
|
- type: cos_sim_ap |
|
|
value: 85.63540257309367 |
|
|
- type: cos_sim_f1 |
|
|
value: 77.9091382258904 |
|
|
- type: cos_sim_precision |
|
|
value: 75.32710280373833 |
|
|
- type: cos_sim_recall |
|
|
value: 80.67446874037573 |
|
|
- type: dot_accuracy |
|
|
value: 88.04478596654636 |
|
|
- type: dot_ap |
|
|
value: 84.16371725220706 |
|
|
- type: dot_f1 |
|
|
value: 76.45949643213666 |
|
|
- type: dot_precision |
|
|
value: 73.54719396827655 |
|
|
- type: dot_recall |
|
|
value: 79.61194949183862 |
|
|
- type: euclidean_accuracy |
|
|
value: 88.9296386851399 |
|
|
- type: euclidean_ap |
|
|
value: 85.71894615274715 |
|
|
- type: euclidean_f1 |
|
|
value: 78.12952767313823 |
|
|
- type: euclidean_precision |
|
|
value: 73.7688098495212 |
|
|
- type: euclidean_recall |
|
|
value: 83.03818909762857 |
|
|
- type: manhattan_accuracy |
|
|
value: 88.89276982186519 |
|
|
- type: manhattan_ap |
|
|
value: 85.6838514059479 |
|
|
- type: manhattan_f1 |
|
|
value: 78.06861875184856 |
|
|
- type: manhattan_precision |
|
|
value: 75.09246088193457 |
|
|
- type: manhattan_recall |
|
|
value: 81.29042192793348 |
|
|
- type: max_accuracy |
|
|
value: 88.9296386851399 |
|
|
- type: max_ap |
|
|
value: 85.71894615274715 |
|
|
- type: max_f1 |
|
|
value: 78.12952767313823 |
|
|
license: mit |
|
|
language: |
|
|
- en |
|
|
--- |
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--- |
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license: mit |
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--- |
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This is the quantized ONNX variant of the [bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) model for embeddings created with [DeepSparse Optimum](https://github.com/neuralmagic/optimum-deepsparse) for ONNX export and Neural Magic's [Sparsify](https://account.neuralmagic.com/signin?client_id=d04a5f0c-983d-11ed-88a6-971073f187d3&return_to=https%3A//accounts.neuralmagic.com/v1/connect/authorize%3Fscope%3Dsparsify%3Aread%2Bsparsify%3Awrite%2Buser%3Aapi-key%3Aread%2Buser%3Aprofile%3Awrite%2Buser%3Aprofile%3Aread%26response_type%3Dcode%26code_challenge_method%3DS256%26redirect_uri%3Dhttps%3A//apps.neuralmagic.com/sparsify/oidc/callback.html%26state%3Da9b466a6193c4a7b92cba469408d2495%26client_id%3Dd04a5f0c-983d-11ed-88a6-971073f187d3%26code_challenge%3DP0EkmKBpplTb7crJOGS8YLSwT8UH-BeuD0wuE4JTORQ%26response_mode%3Dquery) for One-Shot INT8 quantization. |
