BigCode
StarCoder2 15B
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14.7K下载量670点赞Feb 2024发布日期16K tokens上下文BigCode OpenRAIL-M许可证7 入门质量
StarCoder2 15B (15B parameters) requires approximately 13.8 GB of VRAM with Q5_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 StarCoder2 15B on your machine.
Run
docker run --rm -it ghcr.io/ggerganov/llama.cpp:full \
--hf-repo "bigcode/starcoder2-15b" \
--hf-file "starcoder2-15b-Q5_K_M.gguf" \
-c 4096 -ngl 99Quick specs
Parameters15B
Architecturedense
Context16K tokens
Modalitycode
Min RAM5.9 GB
Rec. RAM10.8 GB (Q5_K_M)
LicenseBigCode OpenRAIL-M
FamilyStarCoder2
✓ Code
About this model
- •Model Summary
- •Limitations
- •Training
- •License
- •Citation
相关模型
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最佳硬件
StarCoder2 15B 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
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 5.9 GB | Low | — |
Q3_K_S | 3 | 7.4 GB | Low | — |
NVFP4 | 4 | 8.4 GB | Medium | — |
Q4_K_M | 4 | 9.2 GB | Medium | — |
Q5_K_M | 5 | 10.8 GB | High | — |
Q6_K | 6 | 12.3 GB | High | — |
Q8_0 | 8 | 16.1 GB | Very High | — |
F16 | 16 | 30.7 GB | Maximum | — |
Quality benchmarks
StarCoder2 15B benchmark scores
Coding
SWE-bench Verified—
HumanEval+46.3%
Aider Polyglot—
LiveCodeBench—
Reasoning
MMLU-Pro15.0%
GPQA Diamond3.1%
MATH-5006.0%
ARC Challenge—
General
Chatbot Arena—
IFEval27.8%
Source: official · 2024-02-28
硬件兼容性
全部硬件的适配估算
Computing compatibility...
内存详细分析
Reference: RTX 2060 6GB
Weights10.8 GB
KV Cache1.2 GB
Runtime1.2 GB
Headroom0.6 GB
常见问题
FAQ — StarCoder2 15B
另请参阅