--- pipeline_tag: sentence-similarity tags: - sentence-transformers - feature-extraction - sentence-similarity - mteb model-index: - name: clip-ViT-B-32 results: - task: type: Classification dataset: type: mteb/amazon_counterfactual name: MTEB AmazonCounterfactualClassification (en) config: en split: test revision: e8379541af4e31359cca9fbcf4b00f2671dba205 metrics: - type: accuracy value: 57.999999999999986 - type: ap value: 23.966099106216358 - type: f1 value: 52.8203944454417 - task: type: Classification dataset: type: mteb/amazon_polarity name: MTEB AmazonPolarityClassification config: default split: test revision: e2d317d38cd51312af73b3d32a06d1a08b442046 metrics: - type: accuracy value: 62.366 - type: ap value: 57.98090324593318 - type: f1 value: 61.62762218315074 - task: type: Classification dataset: type: mteb/amazon_reviews_multi name: MTEB AmazonReviewsClassification (en) config: en split: test revision: 1399c76144fd37290681b995c656ef9b2e06e26d metrics: - type: accuracy value: 28.584 - type: f1 value: 28.463306116150783 - task: type: Retrieval dataset: type: arguana name: MTEB ArguAna config: default split: test revision: None metrics: - type: map_at_1 value: 6.259 - type: map_at_10 value: 11.542 - type: map_at_100 value: 12.859000000000002 - type: map_at_1000 value: 12.966 - type: map_at_3 value: 9.128 - type: map_at_5 value: 10.262 - type: mrr_at_1 value: 6.259 - type: mrr_at_10 value: 11.536 - type: mrr_at_100 value: 12.859000000000002 - type: mrr_at_1000 value: 12.967 - type: mrr_at_3 value: 9.128 - type: mrr_at_5 value: 10.262 - type: ndcg_at_1 value: 6.259 - type: ndcg_at_10 value: 15.35 - type: ndcg_at_100 value: 22.107 - type: ndcg_at_1000 value: 25.355 - type: ndcg_at_3 value: 10.172 - type: ndcg_at_5 value: 12.22 - type: precision_at_1 value: 6.259 - type: precision_at_10 value: 2.795 - type: precision_at_100 value: 0.603 - type: precision_at_1000 value: 0.087 - type: precision_at_3 value: 4.41 - type: precision_at_5 value: 3.642 - type: recall_at_1 value: 6.259 - type: recall_at_10 value: 27.951999999999998 - type: recall_at_100 value: 60.313 - type: recall_at_1000 value: 86.771 - type: recall_at_3 value: 13.229 - type: recall_at_5 value: 18.208 - task: type: Clustering dataset: type: mteb/arxiv-clustering-p2p name: MTEB ArxivClusteringP2P config: default split: test revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d metrics: - type: v_measure value: 30.95753257205936 - task: type: Clustering dataset: type: mteb/arxiv-clustering-s2s name: MTEB ArxivClusteringS2S config: default split: test revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 metrics: - type: v_measure value: 26.586511396557583 - task: type: Reranking dataset: type: mteb/askubuntudupquestions-reranking name: MTEB AskUbuntuDupQuestions config: default split: test revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 metrics: - type: map value: 51.090393666506415 - type: mrr value: 65.19412566503979 - task: type: STS dataset: type: mteb/biosses-sts name: MTEB BIOSSES config: default split: test revision: d3fb88f8f02e40887cd149695127462bbcf29b4a metrics: - type: cos_sim_pearson value: 69.9163188743249 - type: cos_sim_spearman value: 64.1345938803495 - type: euclidean_pearson value: 67.36703723549599 - type: euclidean_spearman value: 63.067702100617005 - type: manhattan_pearson value: 71.6901307580259 - type: manhattan_spearman value: 67.04128661733944 - task: type: Classification dataset: type: mteb/banking77 name: MTEB Banking77Classification config: default split: test revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 metrics: - type: accuracy value: 73.22402597402598 - type: f1 value: 73.12739303105114 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-p2p name: MTEB BiorxivClusteringP2P config: default split: test revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 metrics: - type: v_measure value: 28.97385566120484 - task: type: Clustering dataset: type: mteb/biorxiv-clustering-s2s name: MTEB BiorxivClusteringS2S config: default split: test revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 metrics: - type: v_measure value: 27.08579813861177 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackAndroidRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 7.106999999999999 - type: map_at_10 value: 11.797 - type: map_at_100 value: 12.6 - type: map_at_1000 value: 12.711 - type: map_at_3 value: 10.369 - type: map_at_5 value: 10.881 - type: mrr_at_1 value: 9.299 - type: mrr_at_10 value: 15.076 - type: mrr_at_100 value: 15.842 - type: mrr_at_1000 value: 15.928 - type: mrr_at_3 value: 13.4 - type: mrr_at_5 value: 14.044 - type: ndcg_at_1 value: 9.299 - type: ndcg_at_10 value: 15.21 - type: ndcg_at_100 value: 19.374 - type: ndcg_at_1000 value: 22.527 - type: ndcg_at_3 value: 12.383 - type: ndcg_at_5 value: 13.096 - type: precision_at_1 value: 9.299 - type: precision_at_10 value: 3.1620000000000004 - type: precision_at_100 value: 0.662 - type: precision_at_1000 value: 0.11800000000000001 - type: precision_at_3 value: 6.3420000000000005 - type: precision_at_5 value: 4.492 - type: recall_at_1 value: 7.106999999999999 - type: recall_at_10 value: 22.544 - type: recall_at_100 value: 41.002 - type: recall_at_1000 value: 63.67699999999999 - type: recall_at_3 value: 14.316999999999998 - type: recall_at_5 value: 16.367 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackEnglishRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 6.632000000000001 - type: map_at_10 value: 9.067 - type: map_at_100 value: 9.487 - type: map_at_1000 value: 9.563 - type: map_at_3 value: 8.344999999999999 - type: map_at_5 value: 8.742999999999999 - type: mrr_at_1 value: 8.599 - type: mrr_at_10 value: 11.332 - type: mrr_at_100 value: 11.77 - type: mrr_at_1000 value: 11.843 - type: mrr_at_3 value: 10.478 - type: mrr_at_5 value: 10.959000000000001 - type: ndcg_at_1 value: 8.599 - type: ndcg_at_10 value: 10.843 - type: ndcg_at_100 value: 13.023000000000001 - type: ndcg_at_1000 value: 15.409 - type: ndcg_at_3 value: 9.673 - type: ndcg_at_5 value: 10.188 - type: precision_at_1 value: 8.599 - type: precision_at_10 value: 2.038 - type: precision_at_100 value: 0.383 - type: precision_at_1000 value: 0.074 - type: precision_at_3 value: 4.756 - type: precision_at_5 value: 3.3890000000000002 - type: recall_at_1 value: 6.632000000000001 - type: recall_at_10 value: 13.952 - type: recall_at_100 value: 23.966 - type: recall_at_1000 value: 41.411 - type: recall_at_3 value: 10.224 - type: recall_at_5 value: 11.799 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGamingRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 11.153 - type: map_at_10 value: 15.751000000000001 - type: map_at_100 value: 16.464000000000002 - type: map_at_1000 value: 16.561 - type: map_at_3 value: 14.552000000000001 - type: map_at_5 value: 15.136 - type: mrr_at_1 value: 13.041 - type: mrr_at_10 value: 17.777 - type: mrr_at_100 value: 18.427 - type: mrr_at_1000 value: 18.504 - type: mrr_at_3 value: 16.479 - type: mrr_at_5 value: 17.175 - type: ndcg_at_1 value: 13.041 - type: ndcg_at_10 value: 18.581 - type: ndcg_at_100 value: 22.174 - type: ndcg_at_1000 value: 24.795 - type: ndcg_at_3 value: 16.185 - type: ndcg_at_5 value: 17.183 - type: precision_at_1 value: 13.041 - type: precision_at_10 value: 3.2230000000000003 - type: precision_at_100 value: 0.557 - type: precision_at_1000 value: 0.086 - type: precision_at_3 value: 7.544 - type: precision_at_5 value: 5.279 - type: recall_at_1 value: 11.153 - type: recall_at_10 value: 25.052999999999997 - type: recall_at_100 value: 41.521 - type: recall_at_1000 value: 61.138000000000005 - type: recall_at_3 value: 18.673000000000002 - type: recall_at_5 value: 20.964 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackGisRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 5.303 - type: map_at_10 value: 7.649 - type: map_at_100 value: 7.983 - type: map_at_1000 value: 8.067 - type: map_at_3 value: 6.938 - type: map_at_5 value: 7.259 - type: mrr_at_1 value: 5.763 - type: mrr_at_10 value: 8.277 - type: mrr_at_100 value: 8.665000000000001 - type: mrr_at_1000 value: 8.747 - type: mrr_at_3 value: 7.457999999999999 - type: mrr_at_5 value: 7.808 - type: ndcg_at_1 value: 5.763 - type: ndcg_at_10 value: 9.1 - type: ndcg_at_100 value: 11.253 - type: ndcg_at_1000 value: 13.847999999999999 - type: ndcg_at_3 value: 7.521999999999999 - type: ndcg_at_5 value: 8.094 - type: precision_at_1 value: 5.763 - type: precision_at_10 value: 1.514 - type: precision_at_100 value: 0.28700000000000003 - type: precision_at_1000 value: 0.054 - type: precision_at_3 value: 3.277 - type: precision_at_5 value: 2.282 - type: recall_at_1 value: 5.303 - type: recall_at_10 value: 13.126 - type: recall_at_100 value: 23.855 - type: recall_at_1000 value: 44.417 - type: recall_at_3 value: 8.556 - type: recall_at_5 value: 10.006 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackMathematicaRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 2.153 - type: map_at_10 value: 3.447 - type: map_at_100 value: 3.73 - type: map_at_1000 value: 3.8219999999999996 - type: map_at_3 value: 3.0269999999999997 - type: map_at_5 value: 3.283 - type: mrr_at_1 value: 2.612 - type: mrr_at_10 value: 4.289 - type: mrr_at_100 value: 4.6080000000000005 - type: mrr_at_1000 value: 4.713 - type: mrr_at_3 value: 3.669 - type: mrr_at_5 value: 4.005 - type: ndcg_at_1 value: 2.612 - type: ndcg_at_10 value: 4.422000000000001 - type: ndcg_at_100 value: 6.15 - type: ndcg_at_1000 value: 9.25 - type: ndcg_at_3 value: 3.486 - type: ndcg_at_5 value: 3.95 - type: precision_at_1 value: 2.612 - type: precision_at_10 value: 0.8829999999999999 - type: precision_at_100 value: 0.211 - type: precision_at_1000 value: 0.059000000000000004 - type: precision_at_3 value: 1.6580000000000001 - type: precision_at_5 value: 1.294 - type: recall_at_1 value: 2.153 - type: recall_at_10 value: 6.607 - type: recall_at_100 value: 14.707 - type: recall_at_1000 value: 37.99 - type: recall_at_3 value: 4.122 - type: recall_at_5 value: 5.241 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackPhysicsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 7.976999999999999 - type: map_at_10 value: 11.745 - type: map_at_100 value: 12.427000000000001 - type: map_at_1000 value: 12.528 - type: map_at_3 value: 10.478 - type: map_at_5 value: 11.224 - type: mrr_at_1 value: 9.432 - type: mrr_at_10 value: 14.021 - type: mrr_at_100 value: 14.734 - type: mrr_at_1000 value: 14.813 - type: mrr_at_3 value: 12.576 - type: mrr_at_5 value: 13.414000000000001 - type: ndcg_at_1 value: 9.432 - type: ndcg_at_10 value: 14.341000000000001 - type: ndcg_at_100 value: 18.168 - type: ndcg_at_1000 value: 21.129 - type: ndcg_at_3 value: 11.909 - type: ndcg_at_5 value: 13.139999999999999 - type: precision_at_1 value: 9.432 - type: precision_at_10 value: 2.6759999999999997 - type: precision_at_100 value: 0.563 - type: precision_at_1000 value: 0.098 - type: precision_at_3 value: 5.679 - type: precision_at_5 value: 4.216 - type: recall_at_1 value: 7.976999999999999 - type: recall_at_10 value: 19.983999999999998 - type: recall_at_100 value: 37.181 - type: recall_at_1000 value: 58.714999999999996 - type: recall_at_3 value: 13.375 - type: recall_at_5 value: 16.54 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackProgrammersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 5.682 - type: map_at_10 value: 7.817 - type: map_at_100 value: 8.3 - type: map_at_1000 value: 8.378 - type: map_at_3 value: 7.13 - type: map_at_5 value: 7.467 - type: mrr_at_1 value: 6.848999999999999 - type: mrr_at_10 value: 9.687999999999999 - type: mrr_at_100 value: 10.208 - type: mrr_at_1000 value: 10.281 - type: mrr_at_3 value: 8.770999999999999 - type: mrr_at_5 value: 9.256 - type: ndcg_at_1 value: 6.848999999999999 - type: ndcg_at_10 value: 9.519 - type: ndcg_at_100 value: 12.303 - type: ndcg_at_1000 value: 15.004999999999999 - type: ndcg_at_3 value: 8.077 - type: ndcg_at_5 value: 8.656 - type: precision_at_1 value: 6.848999999999999 - type: precision_at_10 value: 1.735 - type: precision_at_100 value: 0.363 - type: precision_at_1000 value: 0.073 - type: precision_at_3 value: 3.7289999999999996 - type: precision_at_5 value: 2.717 - type: recall_at_1 value: 5.682 - type: recall_at_10 value: 13.001 - type: recall_at_100 value: 25.916 - type: recall_at_1000 value: 46.303 - type: recall_at_3 value: 8.949 - type: recall_at_5 value: 10.413 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 5.441 - type: map_at_10 value: 7.997500000000002 - type: map_at_100 value: 8.47225 - type: map_at_1000 value: 8.557083333333333 - type: map_at_3 value: 7.17025 - type: map_at_5 value: 7.597833333333333 - type: mrr_at_1 value: 6.6329166666666675 - type: mrr_at_10 value: 9.596583333333333 - type: mrr_at_100 value: 10.094416666666667 - type: mrr_at_1000 value: 10.171583333333334 - type: mrr_at_3 value: 8.628416666666666 - type: mrr_at_5 value: 9.143416666666667 - type: ndcg_at_1 value: 6.6329166666666675 - type: ndcg_at_10 value: 9.81258333333333 - type: ndcg_at_100 value: 12.459416666666666 - type: ndcg_at_1000 value: 15.099416666666668 - type: ndcg_at_3 value: 8.177499999999998 - type: ndcg_at_5 value: 8.8765 - type: precision_at_1 value: 6.6329166666666675 - type: precision_at_10 value: 1.8355833333333336 - type: precision_at_100 value: 0.38033333333333336 - type: precision_at_1000 value: 0.07358333333333333 - type: precision_at_3 value: 3.912583333333333 - type: precision_at_5 value: 2.8570833333333336 - type: recall_at_1 value: 5.441 - type: recall_at_10 value: 13.79075 - type: recall_at_100 value: 26.12841666666667 - type: recall_at_1000 value: 46.1115 - type: recall_at_3 value: 9.212416666666666 - type: recall_at_5 value: 11.006499999999999 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackStatsRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 4.973000000000001 - type: map_at_10 value: 6.583 - type: map_at_100 value: 7.013999999999999 - type: map_at_1000 value: 7.084 - type: map_at_3 value: 5.987 - type: map_at_5 value: 6.283999999999999 - type: mrr_at_1 value: 6.135 - type: mrr_at_10 value: 7.911 - type: mrr_at_100 value: 8.381 - type: mrr_at_1000 value: 8.451 - type: mrr_at_3 value: 7.234 - type: mrr_at_5 value: 7.595000000000001 - type: ndcg_at_1 value: 6.135 - type: ndcg_at_10 value: 7.8420000000000005 - type: ndcg_at_100 value: 10.335999999999999 - type: ndcg_at_1000 value: 12.742999999999999 - type: ndcg_at_3 value: 6.622 - type: ndcg_at_5 value: 7.156 - type: precision_at_1 value: 6.135 - type: precision_at_10 value: 1.3339999999999999 - type: precision_at_100 value: 0.293 - type: precision_at_1000 value: 0.053 - type: precision_at_3 value: 2.965 - type: precision_at_5 value: 2.086 - type: recall_at_1 value: 4.973000000000001 - type: recall_at_10 value: 10.497 - type: recall_at_100 value: 22.389 - type: recall_at_1000 value: 41.751 - type: recall_at_3 value: 7.248 - type: recall_at_5 value: 8.526 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackTexRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 2.541 - type: map_at_10 value: 4.168 - type: map_at_100 value: 4.492 - type: map_at_1000 value: 4.553 - type: map_at_3 value: 3.62 - type: map_at_5 value: 3.927 - type: mrr_at_1 value: 3.131 - type: mrr_at_10 value: 5.037 - type: mrr_at_100 value: 5.428 - type: mrr_at_1000 value: 5.487 - type: mrr_at_3 value: 4.422000000000001 - type: mrr_at_5 value: 4.752 - type: ndcg_at_1 value: 3.131 - type: ndcg_at_10 value: 5.315 - type: ndcg_at_100 value: 7.207 - type: ndcg_at_1000 value: 9.271 - type: ndcg_at_3 value: 4.244 - type: ndcg_at_5 value: 4.742 - type: precision_at_1 value: 3.131 - type: precision_at_10 value: 1.0699999999999998 - type: precision_at_100 value: 0.247 - type: precision_at_1000 value: 0.053 - type: precision_at_3 value: 2.1340000000000003 - type: precision_at_5 value: 1.624 - type: recall_at_1 value: 2.541 - type: recall_at_10 value: 7.8740000000000006 - type: recall_at_100 value: 16.896 - type: recall_at_1000 value: 32.423 - type: recall_at_3 value: 4.925 - type: recall_at_5 value: 6.181 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackUnixRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 5.58 - type: map_at_10 value: 7.758 - type: map_at_100 value: 8.168000000000001 - type: map_at_1000 value: 8.239 - type: map_at_3 value: 6.895999999999999 - type: map_at_5 value: 7.412000000000001 - type: mrr_at_1 value: 6.81 - type: mrr_at_10 value: 9.295 - type: mrr_at_100 value: 9.763 - type: mrr_at_1000 value: 9.835 - type: mrr_at_3 value: 8.427 - type: mrr_at_5 value: 8.958 - type: ndcg_at_1 value: 6.81 - type: ndcg_at_10 value: 9.436 - type: ndcg_at_100 value: 11.955 - type: ndcg_at_1000 value: 14.387 - type: ndcg_at_3 value: 7.7410000000000005 - type: ndcg_at_5 value: 8.622 - type: precision_at_1 value: 6.81 - type: precision_at_10 value: 1.6230000000000002 - type: precision_at_100 value: 0.335 - type: precision_at_1000 value: 0.062 - type: precision_at_3 value: 3.576 - type: precision_at_5 value: 2.6870000000000003 - type: recall_at_1 value: 5.58 - type: recall_at_10 value: 13.232 - type: recall_at_100 value: 25.233 - type: recall_at_1000 value: 43.864999999999995 - type: recall_at_3 value: 8.549 - type: recall_at_5 value: 10.799 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWebmastersRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 3.8739999999999997 - type: map_at_10 value: 6.491 - type: map_at_100 value: 7.065 - type: map_at_1000 value: 7.185 - type: map_at_3 value: 5.568 - type: map_at_5 value: 6.1080000000000005 - type: mrr_at_1 value: 5.335999999999999 - type: mrr_at_10 value: 8.288 - type: mrr_at_100 value: 8.886 - type: mrr_at_1000 value: 8.976 - type: mrr_at_3 value: 7.115 - type: mrr_at_5 value: 7.846 - type: ndcg_at_1 value: 5.335999999999999 - type: ndcg_at_10 value: 8.463 - type: ndcg_at_100 value: 11.456 - type: ndcg_at_1000 value: 14.662 - type: ndcg_at_3 value: 6.7589999999999995 - type: ndcg_at_5 value: 7.5969999999999995 - type: precision_at_1 value: 5.335999999999999 - type: precision_at_10 value: 1.9369999999999998 - type: precision_at_100 value: 0.498 - type: precision_at_1000 value: 0.116 - type: precision_at_3 value: 3.689 - type: precision_at_5 value: 2.9250000000000003 - type: recall_at_1 value: 3.8739999999999997 - type: recall_at_10 value: 12.281 - type: recall_at_100 value: 26.368000000000002 - type: recall_at_1000 value: 50.422 - type: recall_at_3 value: 7.353 - type: recall_at_5 value: 9.66 - task: type: Retrieval dataset: type: BeIR/cqadupstack name: MTEB CQADupstackWordpressRetrieval config: default split: test revision: None metrics: - type: map_at_1 value: 2.317 - type: map_at_10 value: 3.697 - type: map_at_100 value: 3.9370000000000003 - type: map_at_1000 value: 3.994 - type: map_at_3 value: 3.1329999999999996 - type: map_at_5 value: 3.45 - type: mrr_at_1 value: 2.588 - type: mrr_at_10 value: 4.168 - type: mrr_at_100 value: 4.421 - type: mrr_at_1000 value: 4.481 - type: mrr_at_3 value: 3.512 - type: mrr_at_5 value: 3.909 - type: ndcg_at_1 value: 2.588 - type: ndcg_at_10 value: 4.679 - type: ndcg_at_100 value: 6.114 - type: ndcg_at_1000 value: 8.167 - type: ndcg_at_3 value: 3.5290000000000004 - type: ndcg_at_5 value: 4.093999999999999 - type: precision_at_1 value: 2.588 - type: precision_at_10 value: 0.832 - type: precision_at_100 value: 0.165 - type: precision_at_1000 value: 0.037 - type: precision_at_3 value: 1.6019999999999999 - type: precision_at_5 value: 1.294 - type: recall_at_1 value: 2.317 - type: recall_at_10 value: 7.338 - type: recall_at_100 value: 14.507 - type: recall_at_1000 value: 31.226 - type: recall_at_3 value: 4.258 - type: recall_at_5 value: 5.582 - task: type: Classification dataset: type: mteb/emotion name: MTEB EmotionClassification config: default split: test revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 metrics: - 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type: max_f1 value: 70.90586145648314 --- # clip-ViT-B-32 This is the Image & Text model [CLIP](https://arxiv.org/abs/2103.00020), which maps text and images to a shared vector space. For applications of the models, have a look in our documentation [SBERT.net - Image Search](https://www.sbert.net/examples/applications/image-search/README.html) ## Usage After installing [sentence-transformers](https://sbert.net) (`pip install sentence-transformers`), the usage of this model is easy: ```python from sentence_transformers import SentenceTransformer, util from PIL import Image #Load CLIP model model = SentenceTransformer('clip-ViT-B-32') #Encode an image: img_emb = model.encode(Image.open('two_dogs_in_snow.jpg')) #Encode text descriptions text_emb = model.encode(['Two dogs in the snow', 'A cat on a table', 'A picture of London at night']) #Compute cosine similarities cos_scores = util.cos_sim(img_emb, text_emb) print(cos_scores) ``` See our [SBERT.net - Image Search](https://www.sbert.net/examples/applications/image-search/README.html) documentation for more examples how the model can be used for image search, zero-shot image classification, image clustering and image deduplication. ## Performance In the following table we find the zero-shot ImageNet validation set accuracy: | Model | Top 1 Performance | | --- | :---: | | [clip-ViT-B-32](https://huggingface.co/sentence-transformers/clip-ViT-B-32) | 63.3 | | [clip-ViT-B-16](https://huggingface.co/sentence-transformers/clip-ViT-B-16) | 68.1 | | [clip-ViT-L-14](https://huggingface.co/sentence-transformers/clip-ViT-L-14) | 75.4 | For a multilingual version of the CLIP model for 50+ languages have a look at: [clip-ViT-B-32-multilingual-v1](https://huggingface.co/sentence-transformers/clip-ViT-B-32-multilingual-v1)