| | --- |
| | license: mit |
| | language: |
| | - en |
| | tags: |
| | - mteb |
| | - sparse sparsity quantized onnx embeddings int8 |
| | model-index: |
| | - name: bge-base-en-v1.5-sparse |
| | results: |
| | - task: |
| | type: Classification |
| | dataset: |
| | type: mteb/amazon_counterfactual |
| | name: MTEB AmazonCounterfactualClassification (en) |
| | config: en |
| | split: test |
| | revision: e8379541af4e31359cca9fbcf4b00f2671dba205 |
| | metrics: |
| | - type: accuracy |
| | value: 75.38805970149254 |
| | - type: ap |
| | value: 38.80643435437097 |
| | - type: f1 |
| | value: 69.52906891019036 |
| | - task: |
| | type: Classification |
| | dataset: |
| | type: mteb/amazon_polarity |
| | name: MTEB AmazonPolarityClassification |
| | config: default |
| | split: test |
| | revision: e2d317d38cd51312af73b3d32a06d1a08b442046 |
| | metrics: |
| | - type: accuracy |
| | value: 90.72759999999998 |
| | - type: ap |
| | value: 87.07910150764239 |
| | - type: f1 |
| | value: 90.71025910882096 |
| | - task: |
| | type: Classification |
| | dataset: |
| | type: mteb/amazon_reviews_multi |
| | name: MTEB AmazonReviewsClassification (en) |
| | config: en |
| | split: test |
| | revision: 1399c76144fd37290681b995c656ef9b2e06e26d |
| | metrics: |
| | - type: accuracy |
| | value: 45.494 |
| | - type: f1 |
| | value: 44.917953161904805 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | type: mteb/arxiv-clustering-p2p |
| | name: MTEB ArxivClusteringP2P |
| | config: default |
| | split: test |
| | revision: a122ad7f3f0291bf49cc6f4d32aa80929df69d5d |
| | metrics: |
| | - type: v_measure |
| | value: 46.50495921726095 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | type: mteb/arxiv-clustering-s2s |
| | name: MTEB ArxivClusteringS2S |
| | config: default |
| | split: test |
| | revision: f910caf1a6075f7329cdf8c1a6135696f37dbd53 |
| | metrics: |
| | - type: v_measure |
| | value: 40.080055890804836 |
| | - task: |
| | type: Reranking |
| | dataset: |
| | type: mteb/askubuntudupquestions-reranking |
| | name: MTEB AskUbuntuDupQuestions |
| | config: default |
| | split: test |
| | revision: 2000358ca161889fa9c082cb41daa8dcfb161a54 |
| | metrics: |
| | - type: map |
| | value: 60.22880715757138 |
| | - type: mrr |
| | value: 73.11227630479708 |
| | - task: |
| | type: STS |
| | dataset: |
| | type: mteb/biosses-sts |
| | name: MTEB BIOSSES |
| | config: default |
| | split: test |
| | revision: d3fb88f8f02e40887cd149695127462bbcf29b4a |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 86.9542549153515 |
| | - type: cos_sim_spearman |
| | value: 83.93865958725257 |
| | - type: euclidean_pearson |
| | value: 86.00372707912037 |
| | - type: euclidean_spearman |
| | value: 84.97302050526537 |
| | - type: manhattan_pearson |
| | value: 85.63207676453459 |
| | - type: manhattan_spearman |
| | value: 84.82542678079645 |
| | - task: |
| | type: Classification |
| | dataset: |
| | type: mteb/banking77 |
| | name: MTEB Banking77Classification |
| | config: default |
| | split: test |
| | revision: 0fd18e25b25c072e09e0d92ab615fda904d66300 |
| | metrics: |
| | - type: accuracy |
| | value: 84.29545454545455 |
| | - type: f1 |
| | value: 84.26780483160312 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | type: mteb/biorxiv-clustering-p2p |
| | name: MTEB BiorxivClusteringP2P |
| | config: default |
| | split: test |
| | revision: 65b79d1d13f80053f67aca9498d9402c2d9f1f40 |
| | metrics: |
| | - type: v_measure |
| | value: 36.78678386185847 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | type: mteb/biorxiv-clustering-s2s |
| | name: MTEB BiorxivClusteringS2S |
| | config: default |
| | split: test |
| | revision: 258694dd0231531bc1fd9de6ceb52a0853c6d908 |
| | metrics: |
| | - type: v_measure |
| | value: 34.42462869304013 |
| | - task: |
| | type: Classification |
| | dataset: |
| | type: mteb/emotion |
| | name: MTEB EmotionClassification |
| | config: default |
| | split: test |
| | revision: 4f58c6b202a23cf9a4da393831edf4f9183cad37 |
| | metrics: |
| | - type: accuracy |
| | value: 46.705 |
| | - type: f1 |
| | value: 41.82618717355017 |
| | - task: |
| | type: Classification |
| | dataset: |
| | type: mteb/imdb |
| | name: MTEB ImdbClassification |
| | config: default |
| | split: test |
| | revision: 3d86128a09e091d6018b6d26cad27f2739fc2db7 |
| | metrics: |
| | - type: accuracy |
| | value: 83.14760000000001 |
| | - type: ap |
| | value: 77.40813245635195 |
| | - type: f1 |
| | value: 83.08648833100911 |
| | - task: |
| | type: Classification |
| | dataset: |
| | type: mteb/mtop_domain |
| | name: MTEB MTOPDomainClassification (en) |
| | config: en |
| | split: test |
| | revision: d80d48c1eb48d3562165c59d59d0034df9fff0bf |
| | metrics: |
| | - type: accuracy |
| | value: 92.0519835841313 |
| | - type: f1 |
| | value: 91.73392170858916 |
| | - task: |
| | type: Classification |
| | dataset: |
| | type: mteb/mtop_intent |
| | name: MTEB MTOPIntentClassification (en) |
| | config: en |
| | split: test |
| | revision: ae001d0e6b1228650b7bd1c2c65fb50ad11a8aba |
| | metrics: |
| | - type: accuracy |
| | value: 72.48974008207935 |
| | - type: f1 |
| | value: 54.812872972777505 |
| | - task: |
| | type: Classification |
| | dataset: |
| | type: mteb/amazon_massive_intent |
| | name: MTEB MassiveIntentClassification (en) |
| | config: en |
| | split: test |
| | revision: 31efe3c427b0bae9c22cbb560b8f15491cc6bed7 |
| | metrics: |
| | - type: accuracy |
| | value: 73.17753866846 |
| | - type: f1 |
| | value: 71.51091282373878 |
| | - task: |
| | type: Classification |
| | dataset: |
| | type: mteb/amazon_massive_scenario |
| | name: MTEB MassiveScenarioClassification (en) |
| | config: en |
| | split: test |
| | revision: 7d571f92784cd94a019292a1f45445077d0ef634 |
| | metrics: |
| | - type: accuracy |
| | value: 77.5353059852051 |
| | - type: f1 |
| | value: 77.42427561340143 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | type: mteb/medrxiv-clustering-p2p |
| | name: MTEB MedrxivClusteringP2P |
| | config: default |
| | split: test |
| | revision: e7a26af6f3ae46b30dde8737f02c07b1505bcc73 |
| | metrics: |
| | - type: v_measure |
| | value: 32.00163251745748 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | type: mteb/medrxiv-clustering-s2s |
| | name: MTEB MedrxivClusteringS2S |
| | config: default |
| | split: test |
| | revision: 35191c8c0dca72d8ff3efcd72aa802307d469663 |
| | metrics: |
| | - type: v_measure |
| | value: 30.37879992380756 |
| | - task: |
| | type: Reranking |
| | dataset: |
| | type: mteb/mind_small |
| | name: MTEB MindSmallReranking |
| | config: default |
| | split: test |
| | revision: 3bdac13927fdc888b903db93b2ffdbd90b295a69 |
| | metrics: |
| | - type: map |
| | value: 31.714215488161983 |
| | - type: mrr |
| | value: 32.857362140961904 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | type: mteb/reddit-clustering |
| | name: MTEB RedditClustering |
| | config: default |
| | split: test |
| | revision: 24640382cdbf8abc73003fb0fa6d111a705499eb |
| | metrics: |
| | - type: v_measure |
| | value: 50.99679402527969 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | type: mteb/reddit-clustering-p2p |
| | name: MTEB RedditClusteringP2P |
| | config: default |
| | split: test |
| | revision: 282350215ef01743dc01b456c7f5241fa8937f16 |
| | metrics: |
| | - type: v_measure |
| | value: 59.28024721612242 |
| | - task: |
| | type: STS |
| | dataset: |
| | type: mteb/sickr-sts |
| | name: MTEB SICK-R |
| | config: default |
| | split: test |
| | revision: a6ea5a8cab320b040a23452cc28066d9beae2cee |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 84.54645068673153 |
| | - type: cos_sim_spearman |
| | value: 78.64401947043316 |
| | - type: euclidean_pearson |
| | value: 82.36873285307261 |
| | - type: euclidean_spearman |
| | value: 78.57406974337181 |
| | - type: manhattan_pearson |
| | value: 82.33000263843067 |
| | - type: manhattan_spearman |
| | value: 78.51127629983256 |
| | - task: |
| | type: STS |
| | dataset: |
| | type: mteb/sts12-sts |
| | name: MTEB STS12 |
| | config: default |
| | split: test |
| | revision: a0d554a64d88156834ff5ae9920b964011b16384 |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 83.3001843293691 |
| | - type: cos_sim_spearman |
| | value: 74.87989254109124 |
| | - type: euclidean_pearson |
| | value: 80.88523322810525 |
| | - type: euclidean_spearman |
| | value: 75.6469299496058 |
| | - type: manhattan_pearson |
| | value: 80.8921104008781 |
| | - type: manhattan_spearman |
| | value: 75.65942956132456 |
| | - task: |
| | type: STS |
| | dataset: |
| | type: mteb/sts13-sts |
| | name: MTEB STS13 |
| | config: default |
| | split: test |
| | revision: 7e90230a92c190f1bf69ae9002b8cea547a64cca |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 82.40319855455617 |
| | - type: cos_sim_spearman |
| | value: 83.63807375781141 |
| | - type: euclidean_pearson |
| | value: 83.28557187260904 |
| | - type: euclidean_spearman |
| | value: 83.65223617817439 |
| | - type: manhattan_pearson |
| | value: 83.30411918680012 |
| | - type: manhattan_spearman |
| | value: 83.69204806663276 |
| | - task: |
| | type: STS |
| | dataset: |
| | type: mteb/sts14-sts |
| | name: MTEB STS14 |
| | config: default |
| | split: test |
| | revision: 6031580fec1f6af667f0bd2da0a551cf4f0b2375 |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 83.08942420708404 |
| | - type: cos_sim_spearman |
| | value: 80.39991846857053 |
| | - type: euclidean_pearson |
| | value: 82.68275416568997 |
| | - type: euclidean_spearman |
| | value: 80.49626214786178 |
| | - type: manhattan_pearson |
| | value: 82.62993414444689 |
| | - type: manhattan_spearman |
| | value: 80.44148684748403 |
| | - task: |
| | type: STS |
| | dataset: |
| | type: mteb/sts15-sts |
| | name: MTEB STS15 |
| | config: default |
| | split: test |
| | revision: ae752c7c21bf194d8b67fd573edf7ae58183cbe3 |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 86.70365000096972 |
| | - type: cos_sim_spearman |
| | value: 88.00515486253518 |
| | - type: euclidean_pearson |
| | value: 87.65142168651604 |
| | - type: euclidean_spearman |
| | value: 88.05834854642737 |
| | - type: manhattan_pearson |
| | value: 87.59548659661925 |
| | - type: manhattan_spearman |
| | value: 88.00573237576926 |
| | - task: |
| | type: STS |
| | dataset: |
| | type: mteb/sts16-sts |
| | name: MTEB STS16 |
| | config: default |
| | split: test |
| | revision: 4d8694f8f0e0100860b497b999b3dbed754a0513 |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 82.47886818876728 |
| | - type: cos_sim_spearman |
| | value: 84.30874770680975 |
| | - type: euclidean_pearson |
| | value: 83.74580951498133 |
| | - type: euclidean_spearman |
| | value: 84.60595431454789 |
| | - type: manhattan_pearson |
| | value: 83.74122023121615 |
| | - type: manhattan_spearman |
| | value: 84.60549899361064 |
| | - task: |
| | type: STS |
| | dataset: |
| | type: mteb/sts17-crosslingual-sts |
| | name: MTEB STS17 (en-en) |
| | config: en-en |
| | split: test |
| | revision: af5e6fb845001ecf41f4c1e033ce921939a2a68d |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 87.60257252565631 |
| | - type: cos_sim_spearman |
| | value: 88.29577246271319 |
| | - type: euclidean_pearson |
| | value: 88.25434138634807 |
| | - type: euclidean_spearman |
| | value: 88.06678743723845 |
| | - type: manhattan_pearson |
| | value: 88.3651048848073 |
| | - type: manhattan_spearman |
| | value: 88.23688291108866 |
| | - 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: 61.666254720687206 |
| | - type: cos_sim_spearman |
| | value: 63.83700525419119 |
| | - type: euclidean_pearson |
| | value: 64.36325040161177 |
| | - type: euclidean_spearman |
| | value: 63.99833771224718 |
| | - type: manhattan_pearson |
| | value: 64.01356576965371 |
| | - type: manhattan_spearman |
| | value: 63.7201674202641 |
| | - task: |
| | type: STS |
| | dataset: |
| | type: mteb/stsbenchmark-sts |
| | name: MTEB STSBenchmark |
| | config: default |
| | split: test |
| | revision: b0fddb56ed78048fa8b90373c8a3cfc37b684831 |
| | metrics: |
| | - type: cos_sim_pearson |
| | value: 85.14584232139909 |
| | - type: cos_sim_spearman |
| | value: 85.92570762612142 |
| | - type: euclidean_pearson |
| | value: 86.34291503630607 |
| | - type: euclidean_spearman |
| | value: 86.12670269109282 |
| | - type: manhattan_pearson |
| | value: 86.26109450032494 |
| | - type: manhattan_spearman |
| | value: 86.07665628498633 |
| | - task: |
| | type: Reranking |
| | dataset: |
| | type: mteb/scidocs-reranking |
| | name: MTEB SciDocsRR |
| | config: default |
| | split: test |
| | revision: d3c5e1fc0b855ab6097bf1cda04dd73947d7caab |
| | metrics: |
| | - type: map |
| | value: 84.46430478723548 |
| | - type: mrr |
| | value: 95.63907044299201 |
| | - task: |
| | type: PairClassification |
| | dataset: |
| | type: mteb/sprintduplicatequestions-pairclassification |
| | name: MTEB SprintDuplicateQuestions |
| | config: default |
| | split: test |
| | revision: d66bd1f72af766a5cc4b0ca5e00c162f89e8cc46 |
| | metrics: |
| | - type: cos_sim_accuracy |
| | value: 99.82178217821782 |
| | - type: cos_sim_ap |
| | value: 95.49612561375889 |
| | - type: cos_sim_f1 |
| | value: 91.02691924227318 |
| | - type: cos_sim_precision |
| | value: 90.75546719681908 |
| | - type: cos_sim_recall |
| | value: 91.3 |
| | - type: dot_accuracy |
| | value: 99.67821782178218 |
| | - type: dot_ap |
| | value: 90.55740832326241 |
| | - type: dot_f1 |
| | value: 83.30765279917823 |
| | - type: dot_precision |
| | value: 85.6388595564942 |
| | - type: dot_recall |
| | value: 81.10000000000001 |
| | - type: euclidean_accuracy |
| | value: 99.82475247524752 |
| | - type: euclidean_ap |
| | value: 95.4739426775874 |
| | - type: euclidean_f1 |
| | value: 91.07413010590017 |
| | - type: euclidean_precision |
| | value: 91.8616480162767 |
| | - type: euclidean_recall |
| | value: 90.3 |
| | - type: manhattan_accuracy |
| | value: 99.82376237623762 |
| | - type: manhattan_ap |
| | value: 95.48506891694475 |
| | - type: manhattan_f1 |
| | value: 91.02822580645163 |
| | - type: manhattan_precision |
| | value: 91.76829268292683 |
| | - type: manhattan_recall |
| | value: 90.3 |
| | - type: max_accuracy |
| | value: 99.82475247524752 |
| | - type: max_ap |
| | value: 95.49612561375889 |
| | - type: max_f1 |
| | value: 91.07413010590017 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | type: mteb/stackexchange-clustering |
| | name: MTEB StackExchangeClustering |
| | config: default |
| | split: test |
| | revision: 6cbc1f7b2bc0622f2e39d2c77fa502909748c259 |
| | metrics: |
| | - type: v_measure |
| | value: 60.92486258951404 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | type: mteb/stackexchange-clustering-p2p |
| | name: MTEB StackExchangeClusteringP2P |
| | config: default |
| | split: test |
| | revision: 815ca46b2622cec33ccafc3735d572c266efdb44 |
| | metrics: |
| | - type: v_measure |
| | value: 32.97511013092965 |
| | - task: |
| | type: Reranking |
| | dataset: |
| | type: mteb/stackoverflowdupquestions-reranking |
| | name: MTEB StackOverflowDupQuestions |
| | config: default |
| | split: test |
| | revision: e185fbe320c72810689fc5848eb6114e1ef5ec69 |
| | metrics: |
| | - type: map |
| | value: 52.31647363355174 |
| | - type: mrr |
| | value: 53.26469792462439 |
| | - task: |
| | type: Classification |
| | dataset: |
| | type: mteb/toxic_conversations_50k |
| | name: MTEB ToxicConversationsClassification |
| | config: default |
| | split: test |
| | revision: d7c0de2777da35d6aae2200a62c6e0e5af397c4c |
| | metrics: |
| | - type: accuracy |
| | value: 70.917 |
| | - type: ap |
| | value: 13.760770628090576 |
| | - type: f1 |
| | value: 54.23887489664618 |
| | - task: |
| | type: Classification |
| | dataset: |
| | type: mteb/tweet_sentiment_extraction |
| | name: MTEB TweetSentimentExtractionClassification |
| | config: default |
| | split: test |
| | revision: d604517c81ca91fe16a244d1248fc021f9ecee7a |
| | metrics: |
| | - type: accuracy |
| | value: 59.49349179400113 |
| | - type: f1 |
| | value: 59.815392064510775 |
| | - task: |
| | type: Clustering |
| | dataset: |
| | type: mteb/twentynewsgroups-clustering |
| | name: MTEB TwentyNewsgroupsClustering |
| | config: default |
| | split: test |
| | revision: 6125ec4e24fa026cec8a478383ee943acfbd5449 |
| | metrics: |
| | - type: v_measure |
| | value: 47.29662657485732 |
| | - task: |
| | type: PairClassification |
| | dataset: |
| | type: mteb/twittersemeval2015-pairclassification |
| | name: MTEB TwitterSemEval2015 |
| | config: default |
| | split: test |
| | revision: 70970daeab8776df92f5ea462b6173c0b46fd2d1 |
| | metrics: |
| | - type: cos_sim_accuracy |
| | value: 85.74834594981225 |
| | - type: cos_sim_ap |
| | value: 72.92449226447182 |
| | - type: cos_sim_f1 |
| | value: 68.14611644433363 |
| | - type: cos_sim_precision |
| | value: 64.59465847317419 |
| | - type: cos_sim_recall |
| | value: 72.1108179419525 |
| | - type: dot_accuracy |
| | value: 82.73827263515527 |
| | - type: dot_ap |
| | value: 63.27505594570806 |
| | - type: dot_f1 |
| | value: 61.717543651265 |
| | - type: dot_precision |
| | value: 56.12443292287751 |
| | - type: dot_recall |
| | value: 68.54881266490766 |
| | - type: euclidean_accuracy |
| | value: 85.90332002145796 |
| | - type: euclidean_ap |
| | value: 73.08299660990401 |
| | - type: euclidean_f1 |
| | value: 67.9050313691721 |
| | - type: euclidean_precision |
| | value: 63.6091265268495 |
| | - type: euclidean_recall |
| | value: 72.82321899736148 |
| | - type: manhattan_accuracy |
| | value: 85.87351731537224 |
| | - type: manhattan_ap |
| | value: 73.02205874497865 |
| | - type: manhattan_f1 |
| | value: 67.87532596547871 |
| | - type: manhattan_precision |
| | value: 64.109781843772 |
| | - type: manhattan_recall |
| | value: 72.1108179419525 |
| | - type: max_accuracy |
| | value: 85.90332002145796 |
| | - type: max_ap |
| | value: 73.08299660990401 |
| | - type: max_f1 |
| | value: 68.14611644433363 |
| | - task: |
| | type: PairClassification |
| | dataset: |
| | type: mteb/twitterurlcorpus-pairclassification |
| | name: MTEB TwitterURLCorpus |
| | config: default |
| | split: test |
| | revision: 8b6510b0b1fa4e4c4f879467980e9be563ec1cdf |
| | metrics: |
| | - type: cos_sim_accuracy |
| | value: 88.84231769317343 |
| | - type: cos_sim_ap |
| | value: 85.65683184516553 |
| | - type: cos_sim_f1 |
| | value: 77.60567077973222 |
| | - type: cos_sim_precision |
| | value: 75.6563071297989 |
| | - type: cos_sim_recall |
| | value: 79.65814598090545 |
| | - type: dot_accuracy |
| | value: 86.85333954282609 |
| | - type: dot_ap |
| | value: 80.79899186896125 |
| | - type: dot_f1 |
| | value: 74.15220098146928 |
| | - type: dot_precision |
| | value: 70.70819946919961 |
| | - type: dot_recall |
| | value: 77.94887588543271 |
| | - type: euclidean_accuracy |
| | value: 88.77634183257655 |
| | - type: euclidean_ap |
| | value: 85.67411484805298 |
| | - type: euclidean_f1 |
| | value: 77.61566374357423 |
| | - type: euclidean_precision |
| | value: 76.23255123255123 |
| | - type: euclidean_recall |
| | value: 79.04989220819218 |
| | - type: manhattan_accuracy |
| | value: 88.79962743043428 |
| | - type: manhattan_ap |
| | value: 85.6494795781639 |
| | - type: manhattan_f1 |
| | value: 77.54222877224805 |
| | - type: manhattan_precision |
| | value: 76.14100185528757 |
| | - type: manhattan_recall |
| | value: 78.99599630428088 |
| | - type: max_accuracy |
| | value: 88.84231769317343 |
| | - type: max_ap |
| | value: 85.67411484805298 |
| | - type: max_f1 |
| | value: 77.61566374357423 |
| | --- |
| | |
| | # bge-base-en-v1.5-sparse |
| |
|
| | ## Usage |
| |
|
| | This is the sparse ONNX variant of the [bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) embeddings model accelerated with [Sparsify](https://github.com/neuralmagic/sparsify) for quantization/pruning and [DeepSparseSentenceTransformers](https://github.com/neuralmagic/deepsparse/tree/main/src/deepsparse/sentence_transformers) for inference. |
| |
|
| | ```bash |
| | pip install -U deepsparse-nightly[sentence_transformers] |
| | ``` |
| |
|
| | ```python |
| | from deepsparse.sentence_transformers import DeepSparseSentenceTransformer |
| | model = DeepSparseSentenceTransformer('neuralmagic/bge-base-en-v1.5-sparse', export=False) |
| | |
| | # Our sentences we like to encode |
| | sentences = ['This framework generates embeddings for each input sentence', |
| | 'Sentences are passed as a list of string.', |
| | 'The quick brown fox jumps over the lazy dog.'] |
| | |
| | # Sentences are encoded by calling model.encode() |
| | embeddings = model.encode(sentences) |
| | |
| | # Print the embeddings |
| | for sentence, embedding in zip(sentences, embeddings): |
| | print("Sentence:", sentence) |
| | print("Embedding:", embedding.shape) |
| | print("") |
| | ``` |
| |
|
| | For general questions on these models and sparsification methods, reach out to the engineering team on our [community Slack](https://join.slack.com/t/discuss-neuralmagic/shared_invite/zt-q1a1cnvo-YBoICSIw3L1dmQpjBeDurQ). |
