Comments (4)
prlz77
commented on May 26, 2024
Hi!
It works for me! can you try on another computer network?
Btw, you'll have to revert to a previous version of the code in this repo to make them work (it is written in the README). Whenever I have some GPUs available I will retrain them with the latest code. Or, if you have the resources I'd really appreciate if you could train and send me the model.
Pau
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coallaoh
commented on May 26, 2024
I see - it's not broken. In a new wireless network the download works fine.
Thanks for the instructions. I'm not sure if I'll train the model myself, but if I do I'll surely send you the weights ;)
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iamZe
commented on May 26, 2024
the link seems not working
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prlz77
commented on May 26, 2024
Did you read the last comments? Did you try in another network?
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Related Issues (18)
- Questions about the performances. HOT 23
- GPU memory usage during training HOT 1
- question about the input img size HOT 8
- Sublinear speed-up with dataparallel HOT 1
- Is the D right ? HOT 6
- About initial learning rate HOT 2
- The structure problem
- cannot run inference mismatch sizes HOT 2
- Could you provide the ResNeXt of Caffe version ?
- RuntimeError: Error(s) in loading state_dict for CifarResNeXt: HOT 1
- Can I directly convert TensorFlow's ResNext weight to pytorch's weight and use it directly? HOT 2
- question about the dimension of the net HOT 4
- GPU memory usage HOT 1
- Question about the number of channels HOT 4
- OSError: [Errno 12] Cannot allocate memory HOT 13
- sizes do not match HOT 1
- TypeError: tensor(0, device='cuda:0') is not JSON serializable HOT 3
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