Jina AIJina AI

Jina Embeddings v3

現行
4.0Mダウンロード1.1KいいねSep 2024公開日8K トークンコンテキストCC-BY-NC-4.0ライセンス86 優秀品質

Jina Embeddings v3 (0.5720000267028809B parameters) requires approximately 4.9 GB of VRAM with F16 quantization. For the best balance of quality and speed, we recommend hardware with at least 6 GB of VRAM.

はじめに

— コピー&ペーストでローカル実行

Copy-paste commands to run Jina Embeddings v3 on your machine.

Run

ollama run jina/jina-embeddings-v3

Quick specs

Parameters0.57B
Architecturedense
Context8K tokens
Modalityembedding
Min RAM0.2 GB
Rec. RAM1.2 GB (F16)
LicenseCC-BY-NC-4.0
FamilyJina Embeddings
RAG

About this model

jina-embeddings-v3: Multilingual Embeddings With Task LoRA

  • Extended Sequence Length:: Supports up to 8192 tokens with RoPE
  • Task-Specific Embedding:: Customize embeddings through the task argument with the following options:
  • retrieval.query: Used for query embeddings in asymmetric retrieval tasks
  • retrieval.passage: Used for passage embeddings in asymmetric retrieval tasks
  • separation: Used for embeddings in clustering and re-ranking applications

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おすすめ

最適なハードウェア

Jina Embeddings v3のおすすめ

このモデルを実行

量子化オプション

量子化レベル別VRAM推定値

No hardware detected — fit column shows raw VRAM estimates

QuantBitsVRAMQualityFit
Q2_K
2
0.2 GB
Low
Q3_K_S
3
0.3 GB
Low
NVFP4
4
0.3 GB
Medium
Q4_K_M
4
0.3 GB
Medium
Q5_K_M
5
0.4 GB
High
Q6_K
6
0.5 GB
High
Q8_0
8
0.6 GB
Very High
F16
16
1.2 GB
Maximum

ハードウェア互換性

全ハードウェアの適合度推定

カリキュレーターを開く

Computing compatibility...

メモリ内訳

Reference: RTX 2060 6GB

Weights1.2 GB
KV Cache2.0 GB
Runtime1.2 GB
Headroom0.6 GB

よくある質問

FAQ — Jina Embeddings v3

関連項目