Comments (2)
因为没用到bert的embedding,所以才设置成5。默认为50000,浪费空间,所以就设置一个很小的值,设置为vocab_size=1也行
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因为没用到bert的embedding,所以才设置成5。默认为50000,浪费空间,所以就设置一个很小的值,设置为vocab_size=1也行
好的 非常感谢大佬
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Related Issues (17)
- 关于最后的结果 HOT 1
- Word2Vector和BERT权重必须一致是什么意思 HOT 2
- 有关模型细节的几个疑问 HOT 1
- 有没有搞个基础环境的docker的同学 分享一下 HOT 1
- 弱问下,PPT图中的 连续特征 是什么? HOT 1
- 弱问下,PPT图中的 广告受众人群的性别年龄分布,在预测阶段怎么得到? HOT 12
- 弱问下,PPT图中的 用户点击序列 具体? HOT 1
- 请问其他属性id是如何融入广告id的? HOT 4
- from transformers.modeling_bert import BertLayerNorm HOT 1
- vocab_dim_v1 HOT 3
- 请问python的版本 HOT 2
- 预训练词向量频次过滤问题 HOT 3
- 请问在执行run.py出现找不到文件怎么处理? HOT 3
- 尊敬的作者,请问提供的bert-small是否经过预训练? HOT 1
- 不再尝试,已关闭 HOT 4
- package的版本 HOT 1
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