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| 模型 | 链接 | 链接(国内镜像站) |
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| -- | -- | -- |
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| Qwen3:0.6b | [Qwen3-0.6B-Int8](https://huggingface.co/AXERA-TECH/Qwen3-0.6B) | [Qwen3-0.6B-Int8](https://hf-mirror.com/AXERA-TECH/Qwen3-0.6B) |
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| DeepSeek-R1:1.5b | [DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/AXERA-TECH/DeepSeek-R1-Distill-Qwen-1.5B) | [DeepSeek-R1-Distill-Qwen-1.5B](https://hf-mirror.com/AXERA-TECH/DeepSeek-R1-Distill-Qwen-1.5B) |
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| Qwen2.5:1.5b | [Qwen2.5-1.5B-Instruct-GPTQ-Int8](https://huggingface.co/AXERA-TECH/Qwen2.5-1.5B-Instruct-GPTQ-Int8) | [Qwen2.5-1.5B-Instruct-GPTQ-Int8](https://hf-mirror.com/AXERA-TECH/Qwen2.5-1.5B-Instruct-GPTQ-Int8) |
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| SD1.5 | [lcm-lora-sdv1-5](https://huggingface.co/AXERA-TECH/lcm-lora-sdv1-5) | [lcm-lora-sdv1-5](https://hf-mirror.com/AXERA-TECH/lcm-lora-sdv1-5) |
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**请注意:以上模型都需要基于 `SDK 1.45.0` 版本编译打包出来的镜像才可运行大模型。请及时更新系统,我们提供的 TFCard&eMMC 镜像是符合条件的,且预留了 6GB 内存供模型加载运行使用,可以运行 7b 参数的 int4 大模型。**
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*快速体验 qwen3-0.6b:*
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```bash
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git clone https://hf-mirror.com/AXERA-TECH/Qwen3-0.6B
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pip install transformers jinja2 -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
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cd Qwen3-0.6B
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chmod +x main_ax650
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python3 qwen3_tokenizer_uid.py
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sh run_qwen3_0.6b_int8_ctx_ax650.sh
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```
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## 爱芯元智AX650N部署yolov5s 自定义模型
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> 本博客将向你展示零基础一步步的部署好自己的yolov5s模型(博主展示的是安全帽模型),利用yolov5 官方的代码工具导出onnx模型,并通过onnxsim自带的工具精简网络结构,导出子图,为了Pulsar2 工具进行处理模型做准备。
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