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# Nanbeige4.1-3B
## 论文
[Nanbeige4.1-3B](https://arxiv.org/abs/2602.13367)
## 模型简介
Nanbeige4.1-3B是基于Nanbeige4-3B-Base构建的,是我们之前的推理模型Nanbeige4-3B-Thinking-2511的增强版本。该模型通过进一步的监督微调(SFT)和强化学习(RL)后训练优化而实现。作为小参数量规模下极具竞争力的开源模型,Nanbeige4.1-3B展示了紧凑型模型能够同时实现强大的推理能力、偏好对齐和有效的智能体行为。
<div align=center>
<img src="./doc/perf.jpg"/>
</div>
具体而言,Nanbeige4.1-3B展现出以下核心优势:
**强大推理能力**:Nanbeige4.1-3B能够在单次前向传播中通过持续连贯的推理解决复杂的多步骤问题,并在LiveCodeBench-Pro、IMO-Answer-Bench和AIME 2026 I等具有挑战性的任务上稳定输出正确的最终答案。
**稳健的偏好对齐**:Nanbeige4.1-3B实现了出色的对齐性能,在Arena-Hard-v2和Multi-Challenge基准测试中不仅超越了Qwen3-4B-2507和Nanbeige4-3B-2511等同规模模型,而且显著优于包括Qwen3-30B-A3B和Qwen3-32B在内的更大规模模型。
**智能体能力**:Nanbeige4.1-3B是首个原生支持深度搜索任务并能够稳定处理超过500轮工具调用复杂问题求解的小型通用模型。它填补了小模型生态中长期存在的空白——即模型通常要么针对通用推理进行优化,要么针对智能体场景进行优化,但很少能在两方面都表现卓越。
<div align=center>
<img src="./doc/perf.jpg"/>
</div>
## 环境依赖
| 软件 | 版本 |
| :----------: | :--------------------------------------------: |
| DTK | 26.04.2 |
| python | 3.10.12 |
| transformers | 4.57.6 |
| torch | 2.5.1+das.opt1.dtk2604.20260116.g78471bfd |
| accelerate | 1.12.0 |
| torchvision | 0.20.1+das.opt1.dtk2604.20260116.g65c66897 |
| flash_attn | 2.6.1+das.opt1.dtk2604.20260131.g4edd8bf9 |
| vllm | 0.11.0+das.opt1.rc2.dtk2604.20260128.g0bf89b0c |
推荐使用镜像:harbor.sourcefind.cn:5443/dcu/admin/base/vllm:0.11.0-ubuntu22.04-dtk26.04-0130-py3.10-20260202
- 挂载地址`-v`根据实际模型情况修改
```bash
docker run -it \
--shm-size 60g \
--network=host \
--name Nanbeige4.1 \
--privileged \
--device=/dev/kfd \
--device=/dev/dri \
--device=/dev/mkfd \
--group-add video \
--cap-add=SYS_PTRACE \
--security-opt seccomp=unconfined \
-u root \
-v /opt/hyhal/:/opt/hyhal/:ro \
-v /path/your_code_data/:/path/your_code_data/ \
harbor.sourcefind.cn:5443/dcu/admin/base/vllm:0.11.0-ubuntu22.04-dtk26.04-0130-py3.10-20260202 bash
```
更多镜像可前往[光源](https://sourcefind.cn/#/service-list)下载使用。
关于本项目DCU显卡所需的特殊深度学习库可从[光合](https://developer.sourcefind.cn/tool/)开发者社区下载安装。
## 数据集
`暂无`
## 训练
`暂无`
## 推理
## vllm
#### 单机推理
```bash
## serve启动
可参考vllm_serve.sh脚本
vllm serve Nanbeige/Nanbeige4.1-3B --trust-remote-code --dtype bfloat16 -tp 1 --max-model-len 32768 --port 8010
## client访问
可参考vllm_cilent.sh
curl -X POST "http://localhost:8010/v1/chat/completions" -H "Content-Type: application/json" --data '{
"model": "Nanbeige/Nanbeige4.1-3B",
"messages": [
{
"role": "user",
"content": "中国的首都是什么"
}
]
}'
```
## 效果展示
<div align=center>
<img src="./doc/result.png"/>
</div>
### 精度
`DCU与GPU精度一致,推理框架:vllm。`
## 预训练权重
| **模型名称** | **权重大小** | **DCU型号** | **最低卡数需求** | **下载地址** |
| :------------------: | :----------: | :-----------: | :--------------: | :----------------------------------------------------------: |
| Nanbeige4.1-3B | 3B | K100AI | 1 | [Nanbeige4.1-3B](https://huggingface.co/Nanbeige/Nanbeige4.1-3B) |
## 源码仓库及问题反馈
- https://developer.sourcefind.cn/codes/modelzoo/nanbeige4.1_vllm
## 参考资料
- https://huggingface.co/Nanbeige/Nanbeige4.1-3B
icon.png

62.1 KB

# 模型唯一标识
modelCode=2110
# 模型名称
modelName=Nanbeige4.1_vllm
# 模型描述
modelDescription=Nanbeige4.1-3B是基于Nanbeige4-3B-Base构建的,是我们之前的推理模型Nanbeige4-3B-Thinking-2511的增强版本。
# 应用场景
processType=推理
# 算法类别
appScenario=文本生成
# 框架类型
frameType=vllm
# 加速卡类型
accelerateType=K100AI
curl -X POST "http://localhost:8010/v1/chat/completions" -H "Content-Type: application/json" --data '{
"model": "Nanbeige/Nanbeige4.1-3B",
"messages": [
{
"role": "user",
"content": "中国的首都是什么"
}
]
}'
\ No newline at end of file
vllm serve Nanbeige/Nanbeige4.1-3B --trust-remote-code --dtype bfloat16 -tp 1 --max-model-len 32768 --port 8010
\ No newline at end of file
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