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intfloat/e5-large-v2

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Primitive: /encode · Encode · BERT

Text Embeddings by Weakly-Supervised Contrastive Pre-training. Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei, arXiv 2022

Dense

Overview

Hardware: — drives latency, throughput & cost

Size335M params
Tasks /encode
Licensemit
Languagesen
Latency87 ms
Throughput33.2K tok/s
Cost$0.0067 /1M tok

Cost is approximate — computed from list GPU prices; your actual price depends on the provider you deploy SIE with.

Embedding

Output typesDense
Dimensionsdense: 1,024
Max sequence length512
Inputstext

Benchmarks

CQADupstackPhysicsRetrieval

scientific retrieval en

Duplicate question retrieval from StackExchange Physics

Corpus: 38,314 Queries: 1,039
Quality
ndcg at 10 0.3914
map at 10 0.3351
mrr at 10 0.3867
Performance L4 b1 c16
Corpus 26.5K tok/s
Corpus p50 74.3ms
Query 2.7K tok/s
Query p50 53.9ms
Reference →

CosQA

technology retrieval en

Code search with natural language queries

Corpus: 6,267 Queries: 500
Quality
ndcg at 10 0.3116
map at 10 0.2409
mrr at 10 0.2456
Performance L4 b1 c16
Corpus 13.9K tok/s
Corpus p50 60.1ms
Query 1.4K tok/s
Query p50 57.6ms
Reference →

FiQA2018

finance retrieval en

Financial opinion mining and question answering

Corpus: 57,599 Queries: 648
Quality
ndcg at 10 0.3246
map at 10 0.2588
mrr at 10 0.3993
Performance L4 b1 c16
Corpus 31.6K tok/s
Corpus p50 80.9ms
Query 2.8K tok/s
Query p50 55.5ms
Reference →

LegalBenchConsumerContractsQA

legal retrieval en

Question answering on consumer contracts

Corpus: 153 Queries: 396
Quality
ndcg at 10 0.7491
map at 10 0.6947
mrr at 10 0.6960
Performance L4 b1 c16
Corpus 57.2K tok/s
Corpus p50 140.9ms
Query 3.5K tok/s
Query p50 58.3ms
Reference →

NFCorpus

medical retrieval en

Biomedical literature search from NutritionFacts.org

Corpus: 3,593 Queries: 323
Quality
ndcg at 10 0.3315
map at 10 0.1225
mrr at 10 0.5338
Performance L4 b1 c16
Corpus 42.8K tok/s
Corpus p50 112.1ms
Query 1.3K tok/s
Query p50 53.6ms
Reference →

NanoFiQA2018Retrieval

finance retrieval en

Smaller subset of the FiQA financial QA dataset

Quality
ndcg at 10 0.4531
map at 10 0.3742
mrr at 10 0.5054
Performance L4 b1 c16
Corpus 27.3K tok/s
Corpus p50 86.6ms
Query 2.8K tok/s
Query p50 49.5ms
Reference →

SCIDOCS

scientific retrieval en

Citation prediction, document classification, and recommendation for scientific papers

Corpus: 25,656 Queries: 1,000
Quality
ndcg at 10 0.1157
map at 10 0.0655
mrr at 10 0.2093
Performance L4 b1 c16
Corpus 33.2K tok/s
Corpus p50 86.0ms
Query 2.7K tok/s
Query p50 56.2ms
Reference →

SciFact

scientific retrieval en

Scientific claim verification using research literature

Corpus: 5,183 Queries: 300
Quality
ndcg at 10 0.6588
map at 10 0.6123
mrr at 10 0.6269
Performance L4 b1 c16
Corpus 39.4K tok/s
Corpus p50 108.1ms
Query 3.6K tok/s
Query p50 58.1ms
Reference →

StackOverflowQA

technology retrieval en

Programming question answering from Stack Overflow

Corpus: 19,931 Queries: 1,994
Quality
ndcg at 10 0.8902
map at 10 0.8741
mrr at 10 0.8741
Performance L4 b1 c16
Corpus 39.2K tok/s
Corpus p50 95.0ms
Query 42.1K tok/s
Query p50 107.3ms
Reference →

Open source inference for agents

Open-source inference for the models behind your agents. Run it yourself, or let us run it for you.

Github 3.3K

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