nomic-ai/nomic-embed-text-v2-moe
Primitive: /encode · Encode ·
NomicBERT
This model was presented in the paper Training Sparse Mixture Of Experts Text Embedding Models.
View on Hugging Face → Fine-tuned from nomic-ai/nomic-embed-text-v2-moe-unsupervised
Overview
Hardware: — drives latency, throughput & cost
| Size | 475M params |
|---|---|
| Tasks | /encode |
| License | apache-2.0 |
| Languages | en, es, fr, de, it, pt, pl, nl, tr, ja, vi, ru, id, ar, cs, ro, sv, el, uk, zh, hu, da, no, hi, fi, bg, ko, sk, th, he, ca, lt, fa, ms, sl, lv, mr, bn, sq, cy, be, ml, kn, mk, ur, fy, te, eu, sw, so, sd, uz, co, hr, gu, ce, eo, jv, la, zu, mn, si, ga, ky, tg, my, km, mg, pa, sn, ha, ht, su, gd, ny, ps, ku, am, ig, lo, mi, nn, sm, yi, st, tl, xh, yo, af, ta, tn, ug, az, ba, bs, dv, et, gl, gn, gv, hy |
| Latency | 150 ms |
| Throughput | 13.0K tok/s |
| Cost | $0.017 /1M tok |
Cost is approximate — computed from list GPU prices; your actual price depends on the provider you deploy SIE with.
Embedding
| Output types | Dense |
|---|---|
| Dimensions | dense: 768 |
| Max sequence length | 2,048 |
| Inputs | text |
Benchmarks
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CosQA
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FiQA2018
Financial opinion mining and question answering
LegalBenchConsumerContractsQA
Question answering on consumer contracts
NFCorpus
Biomedical literature search from NutritionFacts.org
NanoFiQA2018Retrieval
Smaller subset of the FiQA financial QA dataset
SCIDOCS
Citation prediction, document classification, and recommendation for scientific papers
SciFact
Scientific claim verification using research literature
StackOverflowQA
Programming question answering from Stack Overflow