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Vicuna 13B

Legado
18.3KDownloads243CurtidasMar 2023Publicado4K tokensContextoLlama 2 CommunityLicença50 BomQualidade

Vicuna 13B (13B parameters) requires approximately 21.9 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 26 GB of VRAM.

Comece agora

— copie e cole para rodar localmente

Copy-paste commands to run Vicuna 13B on your machine.

Run

ollama run vicuna:13b

Quick specs

Parameters13B
Architecturedense
Context4K tokens
Modalitytext
Min RAM5.1 GB
Rec. RAM7.9 GB (Q4_K_M)
LicenseLlama 2 Community
FamilyVicuna
Chat

About this model

Vicuna is a chat assistant trained by fine-tuning Llama 2 on user-shared conversations collected from ShareGPT.

  • Developed by:: LMSYS
  • Model type:: An auto-regressive language model based on the transformer architecture
  • License:: Llama 2 Community License Agreement
  • Finetuned from model:: Llama 2

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Opções de quantização

Estimativas de VRAM por nível de quantização

No hardware detected — fit column shows raw VRAM estimates

QuantBitsVRAMQualityFit
Q2_K
2
5.1 GB
Low
Q3_K_S
3
6.4 GB
Low
NVFP4
4
7.3 GB
Medium
Q4_K_M
4
7.9 GB
Medium
Q5_K_M
5
9.4 GB
High
Q6_K
6
10.7 GB
High
Q8_0
8
13.9 GB
Very High
F16
16
26.7 GB
Maximum

Quality benchmarks

Vicuna 13B benchmark scores

Benchmark verified

Reasoning

MMLU-Pro
GPQA Diamond
MATH-500
ARC Challenge82.2%

Source: community · 2023-07-29

Compatibilidade de hardware

Estimativas de compatibilidade para todo o hardware

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Computing compatibility...

Detalhamento de memória

Reference: RTX 2060 6GB

Weights7.9 GB
KV Cache12.2 GB
Runtime1.2 GB
Headroom0.6 GB

Perguntas frequentes

FAQ — Vicuna 13B

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