LMSYSLMSYS

Vicuna 7B

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126.0KDownloads400LikesMar 2023Veröffentlicht4K TokenKontextLlama 2 CommunityLizenz5 EinstiegQualität

Vicuna 7B (7B parameters) requires approximately 13.9 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 16 GB of VRAM.

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Copy-paste commands to run Vicuna 7B on your machine.

Run

ollama run vicuna

Quick specs

Parameters7B
Architecturedense
Context4K tokens
Modalitytext
Min RAM2.7 GB
Rec. RAM4.3 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

Verwandte Modelle

Deine Hardware

Erkennung...

Schnellauswahl

Beste Hardware

Top-Empfehlungen für Vicuna 7B

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Quantisierungsoptionen

VRAM-Schätzungen nach Quantisierungsstufe

No hardware detected — fit column shows raw VRAM estimates

QuantBitsVRAMQualityFit
Q2_K
2
2.7 GB
Low
Q3_K_S
3
3.4 GB
Low
NVFP4
4
3.9 GB
Medium
Q4_K_M
4
4.3 GB
Medium
Q5_K_M
5
5.0 GB
High
Q6_K
6
5.7 GB
High
Q8_0
8
7.5 GB
Very High
F16
16
14.3 GB
Maximum

Quality benchmarks

Vicuna 7B benchmark scores

Benchmark verified

Reasoning

MMLU-Pro12.7%
GPQA Diamond1.1%
MATH-5001.4%
ARC Challenge74.1%

General

Chatbot Arena
IFEval23.5%

Source: community · 2023-07-29

Hardware-Kompatibilität

Eignungsschätzungen für alle Hardware

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Computing compatibility...

Speicheraufschlüsselung

Reference: RTX 2060 6GB

Weights4.3 GB
KV Cache7.8 GB
Runtime1.2 GB
Headroom0.6 GB

Häufig gestellte Fragen

FAQ — Vicuna 7B

Siehe auch