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Hi, I am trying to retrain the WLDN model with our own datasets, but I don't know how the training dataset (train.cBond_detailed) is made.
This dataset seems to be the part of the predicted result from the WLN model, but I cannot find any script in the repo to do this.
Could you please explain this part to me?
best regards Yunpeng
The text was updated successfully, but these errors were encountered:
Hi Yunpeng,
The notes for usage can be seen here: https://github.com/connorcoley/rexgen_direct/blob/master/rexgen_direct/core_wln_global/notes.txt
Line 36 has the instructions for getting train.cbond_detailed: python nntest_direct.py --test ../data/train.txt.proc --hidden 300 --depth 3 --model model-300-3-direct --checkpoint ckpt-140000 --verbose 1 --detailed 1 > model-300-3-direct/train.cbond_detailed
python nntest_direct.py --test ../data/train.txt.proc --hidden 300 --depth 3 --model model-300-3-direct --checkpoint ckpt-140000 --verbose 1 --detailed 1 > model-300-3-direct/train.cbond_detailed
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Hi, I am trying to retrain the WLDN model with our own datasets, but I don't know how the training dataset (train.cBond_detailed) is made.
This dataset seems to be the part of the predicted result from the WLN model, but I cannot find any script in the repo to do this.
Could you please explain this part to me?
best regards
Yunpeng
The text was updated successfully, but these errors were encountered: