1. Demonstration of running a native LLM on Android device. Now support:
   • Qwen1.5 - 0.5B, 1.8B
   • MiniCPM - 2.7B
   • Octopus V2 - 2B
2. The demo models were uploaded to the drive: https://drive.google.com/drive/folders/1E43ApPcOq3I2xvb9b7aOxazTcR3hn5zK?usp=drive_link
3. After downloading, place the model into the assets folder.
4. Remember to decompress the *.so zip file stored in the libs/arm64-v8a folder.
5. The demo models were converted from ModelScope and underwent code optimizations to achieve extreme execution speed.
6. Therefore, the inputs & outputs of the demo models are slightly different from the original one.
7. The tokenizer.cpp and tokenizer.hpp files originated from the mnn-llm repository.
8. To export the model on your own, please go to the 'Export' folder, follow the comments to replace the original 'modeling_***.py', and then execute the ***_Export.py Python script. Next, quantize / optimize the onnx model by yourself.
9. During the export process of MiniCPM-V, the Resampler always reports an error 'aten::_upsample_bilinear2d_aa' operator not supported, therefore, it is temporarily infeasible to use vision interaction.
10. See more projects: https://dakeqq.github.io/overview/

1. 在Android设备上运行本地LLM的演示。目前支持:
   • Qwen1.5 - 0.5B, 1.8B
   • MiniCPM - 2.7B
   • Octopus V2 - 2B
2. 演示模型已上传至云端硬盘：https://drive.google.com/drive/folders/1E43ApPcOq3I2xvb9b7aOxazTcR3hn5zK?usp=drive_link
3. 百度: https://pan.baidu.com/s/1NHbUyjZ_VC-o62G13KCrSA?pwd=dake 提取码: dake
4. 下载后，请将模型文件放入assets文件夹。
5. 记得解压存放在libs/arm64-v8a文件夹中的*.so压缩文件。
6. 演示模型是从ModelScope转换来的，并经过代码优化，以实现极致执行速度。
7. 因此，演示模型的输入输出与原始模型略有不同。
8. tokenizer.cpp和tokenizer.hpp文件源自mnn-llm仓库。
9. 想自行导出模型请前往“Export”文件夹，按照注释操作取代原模型的“modeling_***.py”，然后执行 ***_Export.py的python脚本。下一步，自己动手量化或优化导出的ONNX模型。
10. 在导出MiniCPM-V的过程中, Resampler总报错“aten::_upsample_bilinear2d_aa”算子不支持，因此暂时无法使用多模态交互。
11. 看更多項目: https://dakeqq.github.io/overview/

(Qwen1.5-1.8B / 1024 Context)