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老师您好,感谢您的工作和分享! 看到目前有base和larege两个模型,想请教下老师,这两个模型是否能支持fine-tune呢?另外,fastnlp中的训练好的模型,能否再次直接载入? 同时看到一些开源工作,不少有支持添加自定义字典,老师您这边会考虑吗? 谢谢
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目前还没找到fine-tune后不影响其他任务性能的解决方案,所以暂时不会添加fine-tune功能;添加自定义词典的功能正在开发、测试,将在1-3周内更新上来
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谢谢您!了解了,看来fine-tune还比较麻烦。fastNLP中提供有基于bert训练的功能,同时可用自主样本进行训练,期待fastHan融合更好。 (1)试了某NLP工具套件,提供有fine-tune功能,但它们的样本标注方式采用自家的(以NER为例)。如果您项目以后考虑fine-tune功能,希望到时考虑通用些的方式
期待自定义词典功能!
请问下目前版本中NER可以支持自定义词典了吗?看了文档中介绍1.6已经将用户词典功能扩充到所有任务,但实际试了下1.7的词典好像对NER任务无效。
s = "在奈雪的茶买饮料" model(s, 'NER') [[['奈雪', 'NS']]] model.add_user_dict(["奈雪的茶"]) model(s, 'NER') [[['奈雪', 'NS']]] model(s, 'NER', use_dict=True) [[['奈雪', 'NS']]]
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老师您好,感谢您的工作和分享!
看到目前有base和larege两个模型,想请教下老师,这两个模型是否能支持fine-tune呢?另外,fastnlp中的训练好的模型,能否再次直接载入?
同时看到一些开源工作,不少有支持添加自定义字典,老师您这边会考虑吗?
谢谢
The text was updated successfully, but these errors were encountered: