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Adrian Lucas Malec

adlumal

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replied to their post 5 days ago

I benchmarked embedding APIs for speed, compared local vs hosted models, and tuned USearch for sub-millisecond retrieval on 143k chunks using only CPU. The post walks through the results, trade-offs, and what I learned about embedding API terms of service. The main motivation for using USearch is that CPU compute is cheap and easy to scale. Blog post: https://huggingface.co/blog/adlumal/lightning-fast-vector-search-for-legal-documents

liked a dataset 6 days ago

cais/hle

authored a paper 9 days ago

The Massive Legal Embedding Benchmark (MLEB)

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Organizations

liked a dataset 6 days ago

cais/hle

Viewer • Updated Sep 10 • 2.5k • 12.2k • 498

liked a model 8 months ago

perplexity-ai/r1-1776

Text Generation • 671B • Updated Feb 26 • 1.12k • 2.32k

liked a model over 1 year ago

intfloat/e5-mistral-7b-instruct

Feature Extraction • 7B • Updated Apr 23, 2024 • 236k • • 549

liked 2 models almost 2 years ago

BAAI/bge-small-en

Feature Extraction • 33.4M • Updated Dec 13, 2023 • 275k • • 80

NousResearch/Nous-Capybara-34B

Text Generation • Updated Dec 28, 2023 • 1.16k • 259

liked a Space almost 2 years ago

MTEB Leaderboard

Embedding Leaderboard

liked 3 models almost 2 years ago

mhdang/dpo-sdxl-text2image-v1

Text-to-Image • Updated Jan 17, 2024 • 232

WhereIsAI/UAE-Large-V1

Feature Extraction • 0.3B • Updated Jul 29 • 916k • • 237

berkeley-nest/Starling-LM-7B-alpha

Text Generation • 7B • Updated Mar 20, 2024 • 1.05k • 554

liked 2 datasets almost 2 years ago

isaacus/open-australian-legal-qa

Viewer • Updated Apr 1 • 2.12k • 294 • 17

isaacus/open-australian-legal-corpus

Viewer • Updated Aug 28 • 147k • 578 • 79