AI开发平台MODELARTS-推理场景介绍:支持的模型列表和权重文件
支持的模型列表和权重文件
本方案支持vLLM的v0.6.0版本。不同vLLM版本支持的模型列表有差异,具体如表3所示。
序号 |
模型名称 |
是否支持fp16/bf16推理 |
是否支持W4A16量化 |
是否支持W8A8量化 |
是否支持W8A16量化 |
是否支持 kv-cache-int8量化 |
开源权重获取地址 |
---|---|---|---|---|---|---|---|
1 |
llama-7b |
√ |
√ |
√ |
√ |
√ |
|
2 |
llama-13b |
√ |
√ |
√ |
√ |
√ |
|
3 |
llama-65b |
√ |
√ |
√ |
√ |
√ |
|
4 |
llama2-7b |
√ |
√ |
√ |
√ |
√ |
|
5 |
llama2-13b |
√ |
√ |
√ |
√ |
√ |
|
6 |
llama2-70b |
√ |
√ |
√ |
√ |
√ |
|
7 |
llama3-8b |
√ |
√ |
√ |
√ |
√ |
|
8 |
llama3-70b |
√ |
√ |
√ |
√ |
√ |
|
9 |
yi-6b |
√ |
√ |
√ |
√ |
√ |
|
10 |
yi-9b |
√ |
√ |
√ |
√ |
√ |
|
11 |
yi-34b |
√ |
√ |
√ |
√ |
√ |
|
12 |
deepseek-llm-7b |
√ |
x |
x |
x |
x |
|
13 |
deepseek-coder-33b-instruct |
√ |
x |
x |
x |
x |
https://huggingface.co/deepseek-ai/deepseek-coder-33b-instruct |
14 |
deepseek-llm-67b |
√ |
x |
x |
x |
x |
|
15 |
qwen-7b |
√ |
√ |
√ |
√ |
x |
|
16 |
qwen-14b |
√ |
√ |
√ |
√ |
x |
|
17 |
qwen-72b |
√ |
√ |
√ |
√ |
x |
|
18 |
qwen1.5-0.5b |
√ |
√ |
√ |
√ |
x |
|
19 |
qwen1.5-7b |
√ |
√ |
√ |
√ |
x |
|
20 |
qwen1.5-1.8b |
√ |
√ |
√ |
√ |
x |
|
21 |
qwen1.5-14b |
√ |
√ |
√ |
√ |
x |
|
22 |
qwen1.5-32b |
√ |
√ |
√ |
√ |
x |
|
23 |
qwen1.5-72b |
√ |
√ |
√ |
√ |
x |
|
24 |
qwen1.5-110b |
√ |
√ |
√ |
√ |
x |
|
25 |
qwen2-0.5b |
√ |
√ |
√ |
√ |
x |
|
26 |
qwen2-1.5b |
√ |
√ |
√ |
√ |
x |
|
27 |
qwen2-7b |
√ |
√ |
x |
√ |
x |
|
28 |
qwen2-72b |
√ |
√ |
√ |
√ |
x |
|
29 |
qwen2.5-0.5b |
√ |
√ |
√ |
√ |
x |
|
30 |
qwen2.5-1.5b |
√ |
√ |
√ |
√ |
x |
|
31 |
qwen2.5-3b |
√ |
√ |
√ |
√ |
x |
|
32 |
qwen2.5-7b |
√ |
√ |
x |
√ |
x |
|
33 |
qwen2.5-14b |
√ |
√ |
√ |
√ |
x |
|
34 |
qwen2.5-32b |
√ |
√ |
√ |
√ |
x |
|
35 |
qwen2.5-72b |
√ |
√ |
√ |
√ |
x |
|
36 |
baichuan2-7b |
√ |
x |
x |
√ |
x |
|
37 |
baichuan2-13b |
√ |
x |
x |
√ |
x |
|
38 |
gemma-2b |
√ |
x |
x |
x |
x |
|
39 |
gemma-7b |
√ |
x |
x |
x |
x |
|
40 |
chatglm2-6b |
√ |
x |
x |
x |
x |
|
41 |
chatglm3-6b |
√ |
x |
x |
x |
x |
|
42 |
glm-4-9b |
√ |
x |
x |
x |
x |
|
43 |
mistral-7b |
√ |
x |
x |
x |
x |
|
44 |
mixtral-8x7b |
√ |
x |
x |
x |
x |
|
45 |
falcon-11b |
√ |
x |
x |
x |
x |
|
46 |
qwen2-57b-a14b |
√ |
x |
x |
x |
x |
|
47 |
llama3.1-8b |
√ |
√ |
√ |
√ |
x |
https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct |
48 |
llama3.1-70b |
√ |
√ |
√ |
√ |
x |
https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct |
49 |
llama-3.1-405B |
√ |
√ |
x |
x |
x |
https://huggingface.co/hugging-quants/Meta-Llama-3.1-405B-Instruct-AWQ-INT4 |
50 |
llama-3.2-1B |
√ |
x |
x |
x |
x |
|
51 |
llama-3.2-3B |
√ |
x |
x |
x |
x |
|
52 |
llava-1.5-7b |
√ |
x |
x |
x |
x |
|
53 |
llava-1.5-13b |
√ |
x |
x |
x |
x |
|
54 |
llava-v1.6-7b |
√ |
x |
x |
x |
x |
https://huggingface.co/llava-hf/llava-v1.6-vicuna-7b-hf/tree/main |
55 |
llava-v1.6-13b |
√ |
x |
x |
x |
x |
https://huggingface.co/llava-hf/llava-v1.6-vicuna-13b-hf/tree/main |
56 |
llava-v1.6-34b |
√ |
x |
x |
x |
x |
|
57 |
internvl2-8B |
√ |
x |
x |
x |
x |
|
58 |
internvl2-26B |
√ |
x |
x |
x |
x |
|
59 |
internvl2-40B |
√ |
x |
x |
x |
x |
|
60 |
MiniCPM-v2.6 |
√ |
x |
x |
x |
x |
|
61 |
deepseek-v2-236b |
x |
x |
√ |
x |
x |
|
62 |
deepseek-v2-lite-16b |
√ |
x |
√ |
x |
x |
|
63 |
qwen2-vl-7B |
√ |
x |
x |
x |
x |
Qwen/Qwen2-VL-7B-Instruct at main (huggingface.co) 注意:Qwen2-VL 开源vllm依赖特定transformers版本, 请手动安装: pip install git+https://github.com/huggingface/transformers.git@21fac7abba2a37fae86106f87fcf9974fd1e3830 |
64 |
qwen-vl |
√ |
x |
x |
x |
x |
|
65 |
qwen-vl-chat |
√ |
x |
x |
x |
x |
|
66 |
MiniCPM-v2 |
√ |
x |
x |
x |
x |
https://huggingface.co/HwwwH/MiniCPM-V-2 注意:需要修改源文件site-packages/timm/layers/pos_embed.py,在第46行上面新增一行代码,如下: posemb = posemb.contiguous() #新增 posemb = F.interpolate(posemb, size=new_size, mode=interpolation, antialias=antialias) |
各模型支持的卡数请参见附录:基于vLLM不同模型推理支持最小卡数和最大序列说明章节。
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