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CodeLlama 7B Instruct

旧版
44.3K下载量258点赞Aug 2023发布日期16K tokens上下文Community许可证56 良好质量

CodeLlama 7B Instruct (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.

快速开始

— 复制粘贴即可本地运行

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

Run

lms load CodeLlama-7b-Instruct-hf && lms server start

Quick specs

Parameters7B
Architecturedense
Context16K tokens
Modalitycode
Min RAM2.7 GB
Rec. RAM4.3 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 7B 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

相关模型

你的硬件

检测中...

快速推荐

最佳硬件

CodeLlama 7B Instruct 的最佳选择

运行此模型

量化选项

各量化级别的 VRAM 估算

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

CodeLlama 7B Instruct benchmark scores

Benchmark verified

Coding

SWE-bench Verified
HumanEval+34.8%
Aider Polyglot
LiveCodeBench

Source: official · 2023-08-24

硬件兼容性

全部硬件的适配估算

打开计算器

Computing compatibility...

内存详细分析

Reference: RTX 2060 6GB

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

常见问题

FAQ — CodeLlama 7B Instruct

另请参阅