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Jina AIJina AI

Jina Embeddings v3

Actual
4.0MDescargas1.1KMe gustaSep 2024Publicado8K tokensContextoCC-BY-NC-4.0Licencia86 FuerteCalidad

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.

Comenzar

— copia y pega para ejecutar en local

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

Tu hardware

Detectando...

Selecciones rápidas

Mejor hardware

Mejores opciones para Jina Embeddings v3

Ejecutar este modelo

Opciones de cuantización

Estimaciones de VRAM por nivel de cuantización

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

Compatibilidad de hardware

Estimaciones de encaje en todo el hardware

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Computing compatibility...

Desglose de memoria

Reference: RTX 2060 6GB

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

Preguntas frecuentes

FAQ — Jina Embeddings v3

Ver también