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CPM-9G-8B
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README.md

方案： 全参数微调，使用不同数据集训练多个模型和推理时增强进行融合。

训练代码： LLaMA-Factory.zip 解压后使用，可参照https://github.com/hiyouga/LLaMA-Factory配置环境，或将代码映射到docker中使用。 训练：train.sh。将数据集放到LLaMA-Factory/data文件夹下，将train.sh放到LLaMA-Factory下使用。 推理： python inference.py(需在inference.py中修改好模型路径。) test_case.json是从题目中提取出来的测试用例。

百度网盘需要收费，使用阿里云盘 model_wight:通过百度网盘分享的文件： https://www.alipan.com/s/FTPWUSBuz7s

docker: https://www.alipan.com/s/FTPWUSBuz7s

train_data: https://www.alipan.com/s/FTPWUSBuz7s