Comments (7)
Did you check that these 4 are installed?
- wget
- unzip
- python3
- pip
Especially when python is installed, it should have a "python3" alias. If these are installed, you can skip the pre-download check code and just run the remaining lines.
from drqa.
Yes, I installed everything, I had to skip the pre-download check. Buy when I do the next comand "python train.py -e 40 -bs 32", give me this error:
File "C:......\DrQA\train.py", line 377, in
main()
File "C:.......\DrQA\train.py", line 21, in main
train, dev, dev_y, embedding, opt = load_data(vars(args))
File "C:........\DrQA\train.py", line 213, in load_data
with open('SQuAD/meta.msgpack', 'rb') as f:
FileNotFoundError: [Errno 2] No such file or directory: 'SQuAD/meta.msgpack'
from drqa.
I dont have the file inside the paste.
from drqa.
I haven't tested my code on Windows. I've no idea what's happening. I'll reply to you maybe next week after I try my code on a windows machine.
from drqa.
Bash is only for Linux-based systems. Maybe you need WSL or something like that to make the script work.
from drqa.
I resolved it. I had to convert the encoding to utf-8. Apreciate ur help :)
from drqa.
Glad to see that. :)
from drqa.
Related Issues (20)
- no model file HOT 2
- Adding Evidence as Database (like wikipedia ) HOT 5
- Only decode on a test set HOT 3
- FileNotFoundError: [Errno 2] No such file or directory: 'SQuAD/meta.msgpack' HOT 6
- How long to run the model for the default params HOT 2
- Is there a way to know the score of the prediction to analyse whether it is right or wrong? HOT 1
- planning to implement Attend It Again paper. HOT 2
- Using DrQA on an Chinese dataset HOT 3
- using DrQA for Squad 2.0 and other datasets HOT 1
- train stop HOT 3
- Finetune against a custom dataset HOT 1
- AssertionError: Torch not compiled with CUDA enabled HOT 2
- Regarding train.py HOT 2
- msgpack.exceptions.UnpackValueError: Unpack failed: error = 0 HOT 1
- Trying to understand the index_answer funtion HOT 6
- Getting low F1 and EM scores HOT 1
- Different function of evaluating metrics
- Gradient flow of the failing model
- training stopped at epoch 1 HOT 9
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