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你好，我按[here](https://github.com/zjunlp/DeepKE/blob/main/README_CNSCHEMA.md)中的指示完成了DeepKE-cnSchema开箱即用版的环境配置。对于一些简短的句子，往往只有两个实体、关系词明确的情况下，程序可以正确预测其中的关系。但是对于稍长、实体略多的情况，这个关系抽取给出的结果比较离谱，而且置信度还挺高。
这里是我pr…
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你好，请问训练好的模型应该是bert.ckpt文件吧，这个文件请问要怎么用来进行预测呢，这个是pytorch保存的模型文件吗
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运行sh脚本总会出现未识别的参数**main.py: error: unrecognized arguments: --accum-freq=1**，脚本和示例一模一样
```
`usage: main.py [-h] --train-data TRAIN_DATA [--val-data VAL_DATA] [--num-workers NUM_WORKERS] [--logs LOGS] …
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D:\Bert-Chinese-Text-Classification-Pytorch\pytorch_pretrained\optimization.py:275: UserWarning: This overload of add_ is deprecated:
add_(Number alpha, Tensor other)
Consider using one of the follo…
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谢谢您的代码，数据处理完后，运行train.py，有配置json和预训练模型，我是不是nlp方向的的小白，想试试，求指点，这个目录从哪里获取
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将输出类别个数等于label数
_Originally posted by @daonna in https://github.com/649453932/Bert-Chinese-Text-Classification-Pytorch/issues/17#issuecomment-569576271_
我这边也是类似问题，但是就是主要在于class中放了22行，并且也是0-21数labe…
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Using Context-word-enbedding augmenter:
English:
```python
text = 'hi how are you'
context_aug = naw.ContextualWordEmbsAug(
model_path='bert-base-uncased', action="substitute")
augmented_t…
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hi @nreimers , it's a nice repo. When I read your code in training_stsbenchmark_bilstm.py. I want to test the performance of bert + bilstm, but maybe there is a bug in lstm. I have read all issues abo…
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Hi, thank you for your great work.
distiluse-base-multilingual-cased has one more dense layer compared to the pool-only model. How is this dense layer added?
We are constructing a Chinese long text…
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The log is as follow:
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