LMSYS
Vicuna 13B
Legacy
18.3KDownloads243LikesMar 2023Veröffentlicht4K TokenKontextLlama 2 CommunityLizenz50 GutQualität
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.
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— kopieren & einfügen, um lokal auszuführenCopy-paste commands to run Vicuna 13B on your machine.
Run
ollama run vicuna:13bQuick 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
- •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
Schnellauswahl
Beste Hardware
Top-Empfehlungen für Vicuna 13B
Dieses Modell ausführen
Quantisierungsoptionen
VRAM-Schätzungen nach Quantisierungsstufe
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
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
Reasoning
MMLU-Pro—
GPQA Diamond—
MATH-500—
ARC Challenge82.2%
Source: community · 2023-07-29
Hardware-Kompatibilität
Eignungsschätzungen für alle Hardware
Computing compatibility...
Speicheraufschlüsselung
Reference: RTX 2060 6GB
Weights7.9 GB
KV Cache12.2 GB
Runtime1.2 GB
Headroom0.6 GB
Häufig gestellte Fragen
FAQ — Vicuna 13B
Siehe auch