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CodeLlama 13B Instruct

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3.5KDownloads160LikesAug 2023Veröffentlicht16K TokenKontextCommunityLizenz60 GutQualität

CodeLlama 13B Instruct (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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Copy-paste commands to run CodeLlama 13B Instruct on your machine.

Run

lms load CodeLlama-13b-Instruct-hf && lms server start

Quick specs

Parameters13B
Architecturedense
Context16K tokens
Modalitycode
Min RAM5.1 GB
Rec. RAM7.9 GB (Q4_K_M)
LicenseCommunity
FamilyCodeLlama
Code

About this model

Code Llama is a collection of pretrained and fine-tuned generative text models ranging in scale from 7 billion to 34 billion parameters. This is the repository for the 13 instruct-tuned version in the Hugging Face Transformers format. This model is designed for general code synthesis and understanding. Links to other models can be found in the index at the bottom.

  • [x] Code completion
  • [x] Instructions / chat
  • [ ] Python specialist

Verwandte Modelle

Deine Hardware

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Schnellauswahl

Beste Hardware

Top-Empfehlungen für CodeLlama 13B Instruct

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Quantisierungsoptionen

VRAM-Schätzungen nach Quantisierungsstufe

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

CodeLlama 13B Instruct benchmark scores

Benchmark verified

Coding

SWE-bench Verified
HumanEval+42.7%
Aider Polyglot
LiveCodeBench

Source: official · 2023-08-24

Hardware-Kompatibilität

Eignungsschätzungen für alle Hardware

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Computing compatibility...

Speicheraufschlüsselung

Reference: RTX 2060 6GB

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

Häufig gestellte Fragen

FAQ — CodeLlama 13B Instruct

Siehe auch