Comments (4)
Go4miii
commented on July 28, 2024
由于切换不同的专家模式需给模型加载不同的lora，这与为了提高用户体验的并发处理请求相冲突。在demo中，我们最终采用训练过的全参数模型，解决并发处理下不同专家模式的冲突。你那边如果下载的是四个lora的模型，是会跟全参数模型有一些区别的。
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Sinica1997
commented on July 28, 2024
好的谢谢，那我这里使用全参数的模型就会一致了吗
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Go4miii
commented on July 28, 2024
是的，你可以试一下。
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Sinica1997
commented on July 28, 2024
想再请问一下 ，在demo中你们如何处理多个用户的并发请求呢，是排队等待嘛
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Related Issues (20)
- One small problem HOT 1
- performance issue HOT 2
- 读入huggingface模型报错 HOT 1
- DISC-FinLLM-SFT 完整训练数据（ToDo） HOT 3
- 模型下载到本地后，运行报网络连接错误 HOT 4
- 请问项目的数据集可以公开么?
- 请问可以提供下 FinGPTV3 的评测代码吗？ HOT 1
- 请问模型支持的最大长度是多少；金融知识检索这个功能要怎么使用，web_demo.py文件里找不到对应功能
- Demo无法使用
- 能开源完整代码吗？包括训练和检索增强部分？
- 请问什么时候可以公开金融SFT数据集？
- 尝试autoeval , 评估chatglm2-6b,baichuan-7b 相同的错误如下： HOT 2
- Could DISC provide a pre-8bit-quantized LLM model for those whose Memory is too small HOT 1
- 公开金融SFT数据集下载 HOT 3
- [Not Issue] Will you try MOE like Mixtral-8X7B? HOT 1
- 在提供的eval复现出来结果和给出的结果有一点差距呢
- 期待公开完整数据集^_^
- Financial Calculation是如何使用的？ HOT 2
- 此项目所用的数据总量是496.000KB吗
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