Comments (5)
I solved it by using different bert file.
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I solved it by using different bert file.
would you please say more details about this? how to use different bert file?
from sqlova.
I solved it by using different bert file.
would you please say more details about this? how to use different bert file?
I do not remeber it now that which file I have used. So, I will try to help from my memory.
In the last section of the README, they have described that "bert/convert_tf_checkpoint_to_pytorch.py is from the previous version of huggingface-pytorch-pretrained-BERT, and current version of pytorch-pretrained-BERT is not compatible with the bert model used in this repo due to the difference in variable names (in LayerNorm). See this for the detail."
So, maybe I have not used the same BERT file which they are using. I think they have used "uncased_L-12_H-768_A-12", I mush have used some other model.
from sqlova.
I solved it by using different bert file.
would you please say more details about this? how to use different bert file?
I do not remeber it now that which file I have used. So, I will try to help from my memory.
In the last section of the README, they have described that "bert/convert_tf_checkpoint_to_pytorch.py is from the previous version of huggingface-pytorch-pretrained-BERT, and current version of pytorch-pretrained-BERT is not compatible with the bert model used in this repo due to the difference in variable names (in LayerNorm). See this for the detail."So, maybe I have not used the same BERT file which they are using. I think they have used "uncased_L-12_H-768_A-12", I mush have used some other model.
Thank you so much for your prompt help! I will try if this can solve my problem
from sqlova.
I solved it by using different bert file.
would you please say more details about this? how to use different bert file?
I do not remeber it now that which file I have used. So, I will try to help from my memory.
In the last section of the README, they have described that "bert/convert_tf_checkpoint_to_pytorch.py is from the previous version of huggingface-pytorch-pretrained-BERT, and current version of pytorch-pretrained-BERT is not compatible with the bert model used in this repo due to the difference in variable names (in LayerNorm). See this for the detail."
So, maybe I have not used the same BERT file which they are using. I think they have used "uncased_L-12_H-768_A-12", I mush have used some other model.Thank you so much for your prompt help! I will try if this can solve my problem
Hi, did you resolve this issue ? I'm working on it and facing same issue.
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Related Issues (20)
- Typos in ReadMe.md
- How can I have a look at the ftable1.csv and ftable2.csv
- For real industrial application, what strategy to locate the exact table? HOT 1
- How to fine tune sequence-to-SQL?
- How do I use predict.py for custom data? HOT 2
- weird error occurs when run predict.py
- Testing models with predict.py does not give me any results file HOT 1
- Need of results_train.jsonl
- Standford coreNLP
- Training on custom data HOT 4
- Replicating dev results on BERT base
- Training doesn't run + how to predict with custom query? HOT 1
- Keras implementation of Column Attention
- Error with annotate_ws.py HOT 7
- Isuue in utlis.wikisql.py
- TypeError: 'Document' object is not iterable
- There is insufficient memory during training, and the get_wemb_bert function call in the train function applies for a lot of memory
- dbengine HOT 5
- How to use RoBERTa instead of BERT ?
- How can I evaluate the pre-trained model on WikiSQL? HOT 1
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