git-disl / bert4eth Goto Github PK

Hello,
I set the parameters as written in the readme, but could not detect phishing accounts. If you don't mind, can you give me some trained models, or examples.
Thank you.

i try to run code in my local enveriment，but i have some version problem.

"TypeError: init() got multiple values for argument 'activation'"
when i try to run the "run_pretrain.py".
i try 1.x tf and 2.x tf all can not work.

Hello,
It would be very nice of you if you added the testing files that are mentioned in the README.md.
Thanks.

Hello,

I'm getting that error when running
python gen_pretrain_data.py --bizdate=bert4eth_exp --max_seq_length=100 --dupe_factor=10 --masked_lm_prob=0.8

Traceback (most recent call last):
  File "$PATH\BERT4ETH\Model\gen_pretrain_data.py", line 448, in <module>
    main()
  File "$PATH\BERT4ETH\Model\gen_pretrain_data.py", line 402, in main
    seqs = np.random.permutation(seqs)
  File "mtrand.pyx", line 4703, in numpy.random.mtrand.RandomState.permutation
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (631617,) + inhomogeneous part.

I'm wondering whether we should add a classifier and then train that and 1 or 2 layers of bert4eth using our data set of labels or would it make more sense to somehow use the deanonamization as demonstrated w the ENS example as a first step, perhaps checking to see if it predicted these labels.

Any suggestions would be great as of course the permutations are vast - and time is short

The code should be able to reproduce the results presented in the paper.

Hello, that's a great job!
Could you possibly tell me the detail information about the environmental version in your experiment? like the version of OS, Tensorflow, CUDA, cuDNN and TensorRT.
Thank You.