Comments (7)
不好意思,我没太理解您的意思。能否再向您请教一下:
- 您说的这个模型地址出错,是指pipeline中的调用出现错误了吗?
- 这种错误是发生在训练的过程中,还是在执行预测的过程中产生的呢?
- 如果是训练的过程中出现的问题,需要修改的是yaml配置文件,还是源码本身呢
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补充一下:
我目前调用的任务是做named_entity_recognition, 但是在调试追踪的时候发现,pipeline里总是会调用到text_classification的步骤,用作者官方提供的训练配置训练后,也会出现这种错误的调用链
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还有paddlenlp里面的taskflow也是,超出512也会返回大于512以后的位置。希望可以修改一下后处理代码
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请问一下,训练好的模型在用这个方法调用的时候,一直出现如下报错:
KeyError: "SequenceLabelingPipeline: 'text-classification is not in the models registry group token-classification. Please make sure the correct version of ModelScope library is used.'"
以及
KeyError: 'text-classification is not in the models registry group token-classification. Please make sure the correct version of ModelScope library is used.'
我目前使用的modelscope是1.9.2,一直没搞懂错在哪里,请问你有遇到过类似的报错吗
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模型地址传错了
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你看官方的,你的可能老版本,传参问题
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也是NER任务,自己微调后,遇到了与三楼同样的问题
KeyError: "SequenceLabelingPipeline: 'text-classification is not in the models registry group token-classification. Please make sure the correct version of ModelScope library is used.'"
我的modelscope版本是1.9.3
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