Nomic Embed v2

Free.ai (self-hosted) · embeddings · ~100 tokens per call

Nomic Embed v2 ni an Ìjádé àwọn ààtòjútó ti a ṣe nipasẹ Nomic AI. O ti wa ni Retrieval augmented generation with flexible vector sizes.. Ààyè àìṣàfilọ́lẹ̀ fún ara rẹ̀ ní àwọn GPUs Free.ai — láàyè láti pàtó àwọn ààyè àìṣàfilọ́lẹ̀ rẹ̀ ní ọjọ́ (100 ààyè Àwọn àgbéwọlé). Ti fi silẹ labẹ Apache 2.0 - lilo iṣowo ti gba laaye lori Free.ai.

Àwọn Àgbègbè Tí A Fẹ̀

Nomic Embed v2 converts text into a dense vector (a list of floats) that captures meaning. Use it for semantic search, clustering, recommendation, retrieval-augmented generation (RAG), and any task where "is this text similar to that text" matters.

Àwọn ìṣàmúlò-ètò tí a lò ní 384, 768, 1024, tàbí 1536 nípa ìpéwọ̀n. BGE-M3 ń fi 1024-dim pamọ́; OpenAI Ada ń fi 1536 pamọ́. Àwọn ìṣàmúlò-ètò API ń fi ìṣàmúlò-ètò pamọ́ láti jẹ́ pé àwọn DB vector rẹ̀ ń yan àwọn ìpéwọ̀n àìdálẹ̀ tó yẹ.

Àwọn àwòrán ìdáràn tí a tí fi pamọ́ (gẹ́gẹ́ bí àwọn àwọn ìkúndùǹ tí o jú lọ ni Free.ai) tí a tí kọ́ nípa àwọn àwọn ìtàn 100+. Àwọn iṣẹ́ ìṣàfilọ́lẹ̀ ìtàn-ìtàn - ìṣàfihàn nínú Ingẹ̀ẹ̀lì, ìdáràn àwọn àkọsílẹ̀ nínú Espáñ.

512 si 8,192 tokens dáju àwọn móòdù. Àwọn ìṣàmúlò-ètò tí o jú jú ní àwọn àgbèwọlé - àwọn àkọsílẹ̀ ìjánu-ìjánú nínú àwọn àpéjúwe tí o jú jú ìṣàfarawé.

Nomic Embed v2 n ṣiṣẹ lori GPUs wa ati pe o wa laarin awọn irinṣẹ ti o dara julọ - nipa ~100 awọn ifihan agbara fun ipe kan ti a gbe lati pool ọfẹ ọjọgbọn rẹ. $5 = 200K awọn ifihan agbara.

Yes - POST a list of strings to /v1/embeddings/ and Nomic Embed v2 returns a list of vectors in the same order. Batch size up to 2,048 per request.

L2-normalized nípa ìpéwọ̀n - cosine similarity = dot product. Pass `normalize=false` tí o bà fẹ́ àwọn bètórí àìdálẹ̀ fún àwọn ààyè-iṣẹ́ àwọn ààyè-iṣẹ́ àìdálẹ̀.

Àwọn - Pinecone, Weaviate, Qdrant, Chroma, pgvector, FAISS, LanceDB. Nomic Embed v2 gba àwọn ààyè JSON àìdálẹ̀ padà; DB kò rí àwọn ìṣàmúlò-ètò.

Ya - POST sí /v1/embeddings/ láti inú àwòrán "Nomic Embed v2". Àwọn àgbékalẹ̀ àwọn àgbékalẹ̀ OpenAI, láti jẹ́ pé àwọn láàbùrẹ̀tì klìentì tí wa ní àwọn iṣẹ́ àìdá. /api/ ní àwọn àgbèkalẹ̀ ìṣàfarawé.

Self-hosted models keep your text on our GPUs and discard it after the call returns. Premium pass through with a DPA. We do not train on your inputs.

Sub-100ms fun àkọlé àkókó nípa ààyè-ara-ẹni-nípa, 100-500ms nípa àwọn. Agbègbè àwọn ayẹyẹ́ tí a fi pọ̀ jú lọ nípa àwọn - 1,000 chunks tí a tí pari nínú àwọn ìsàlẹ̀-ilà 2-10.

Ya - Free.ai gba lórí ìlòòdù àwọn ìṣàmúlò-ètò. Ṣẹ̀dà ìṣàfihàn ìṣàfarawékọ́, àwọn pánẹ́ẹ̀lì RAG, àwọn ìṣàmúlò-ètò ìṣàmúlò-ètò àti àwọn à

Nomic Embed v2

Àwọn Àgbègbè Tí A Fẹ̀

Kini Nomic Embed v2 n ṣe?

Ìwọ̀n wo nínú àwọn ìṣàfarawé àwọn ààyè-iṣẹ́ Nomic Embed v2?

Àwọn àwọn ìṣàmúlò-ètò Nomic Embed v2

What is the max input length for Nomic Embed v2?

Ìgbà wo ní Nomic Embed v2 náà gbà?

Can I batch embed with Nomic Embed v2?

Does Nomic Embed v2 normalize the vectors?

Àwọn DB vector wo ní n ṣiṣẹ́ láti Nomic Embed v2?

Àwọn ààyè-iṣẹ́ fún Nomic Embed v2

Kini ìròyìn tí mo bá fi àkọlé àìdálẹ̀ pamọ́ láti inú Nomic Embed v2?

Ìgbà wo ní Nomic Embed v2 náà gba nínú awáròyìn kan?

Ń lè ló àwọn àkóónú Nomic Embed v2 nípa ìṣàfihàn àìṣàmúlò-ètò?

30,000 Free Tokens, Gbogbo ọjọ

Wá: 30K tí a fi pamọ́/ọ̀jọ́!

Kò lè fi pamọ́