wim7

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有遇到这个情况的没?使用vllm多卡是可以的,fschat多卡就是乱码

> > ![image](https://private-user-images.githubusercontent.com/95208496/330375788-02b0508d-2817-4e36-991a-6ba63d75cc9c.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.WEbRE3u_ARTOl9YcW3Ty06Zr_cnWHSs-hv_I8LWKjCg) 看到SearchParam的withFloatVectors方法,入参是‘’Float‘’ ,用float的话,会导致精度丢失,这个有什么解决方案吗? > > 为什么用float会导致精度丢失?据我所知还没有用double向量的模型 float精度只有小数点后7位,milvus存储的向量和embedding转化的向量都不止这些。 存储的向量: ![image](https://github.com/milvus-io/milvus-sdk-java/assets/95208496/152020d7-ecd1-487b-bbc5-3bb772261e17) embedding转化的向量: ![image](https://github.com/milvus-io/milvus-sdk-java/assets/95208496/78315b62-66b4-4cfc-9113-aa09930f35e2) 然后查询的时候只能用float的话,其实是会把精度丢失掉

> > > > ![image](https://private-user-images.githubusercontent.com/95208496/330375788-02b0508d-2817-4e36-991a-6ba63d75cc9c.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.WEbRE3u_ARTOl9YcW3Ty06Zr_cnWHSs-hv_I8LWKjCg) 看到SearchParam的withFloatVectors方法,入参是‘’Float‘’ ,用float的话,会导致精度丢失,这个有什么解决方案吗? > > > > > > > > > 为什么用float会导致精度丢失?据我所知还没有用double向量的模型 > > > > > > float精度只有小数点后7位,milvus存储的向量和embedding转化的向量都不止这些。 存储的向量: ![image](https://private-user-images.githubusercontent.com/95208496/330630910-152020d7-ecd1-487b-bbc5-3bb772261e17.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.enNdmXhtWsqlvSqE48P4KlxdVGzIdhJJ3qFSrQmSoms) embedding转化的向量: ![image](https://private-user-images.githubusercontent.com/95208496/330632126-78315b62-66b4-4cfc-9113-aa09930f35e2.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.Y-_MeJCjn20I766OtIsi2jiGiYhB_7N-0stVQD_NoNk) > >...

> > 大概率你这个数据存错了,用了double格式。这点精度对于搜索不会有任何区别 > > 经过提醒。我查看了代码。没有用double,因为定义集合时设置了向量类型是FloatVector,在存储数据时,不能用double格式的,那样会产生“Type mismatch for field 'feature': Float vector field's value type must be List”错误,所以用的List。然后存储的时候向量值是 ![企业微信截图_17163654011856](https://private-user-images.githubusercontent.com/74177936/332715085-e602d200-b30f-4145-9664-96e41ba7e2c4.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.aJ6tks6FCORgU47kvY1anvMnMUSc2fpKuXI7FYMDUZ0) ,但是在milvus的可视化平台中,存储的向量值和postman中发送的请求参数一致。 ![企业微信截图_17163652912278](https://private-user-images.githubusercontent.com/74177936/332715144-c490639a-6450-4606-ae37-c540ac5fd8d5.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MTYzNjkzMTUsIm5iZiI6MTcxNjM2OTAxNSwicGF0aCI6Ii83NDE3NzkzNi8zMzI3MTUxNDQtYzQ5MDYzOWEtNjQ1MC00NjA2LWFlMzctYzU0MGFjNWZkOGQ1LnBuZz9YLUFtei1BbGdvcml0aG09QVdTNC1ITUFDLVNIQTI1NiZYLUFtei1DcmVkZW50aWFsPUFLSUFWQ09EWUxTQTUzUFFLNFpBJTJGMjAyNDA1MjIlMkZ1cy1lYXN0LTElMkZzMyUyRmF3czRfcmVxdWVzdCZYLUFtei1EYXRlPTIwMjQwNTIyVDA5MTAxNVomWC1BbXotRXhwaXJlcz0zMDAmWC1BbXotU2lnbmF0dXJlPTAzZjFlOWQ4YjhiMTk0NzFkMDZjZTBhMjJjNzdkMTY5ODVjZTM5NDM5MzM3ZTcyY2Y1MjU1M2JiZmQ2YTZkNDkmWC1BbXotU2lnbmVkSGVhZGVycz1ob3N0JmFjdG9yX2lkPTAma2V5X2lkPTAmcmVwb19pZD0wIn0.g-lFo7JO0OOmRkBuHCBBLvkne0Ev_FCsh0oq5e2yBdw) 他们目前不支持double,至于attu客户端显示的向量小数位数,是因为js会自动补小数,并不能当真。

V1.0.1: ![Image](https://github.com/user-attachments/assets/c7a55b74-0e04-4193-bfb2-583d1b35bce4) V0.15.3:

The significance of using this tool is that some files are not mandatory. If I directly use file extraction nodes without uploading files, there will be errors. After I encapsulate...

> > The significance of using this tool is that some files are not mandatory. If I directly use file extraction nodes without uploading files, there will be errors. After...

> > > The significance of using this tool is that some files are not mandatory. If I directly use file extraction nodes without uploading files, there will be errors....