Error pushing models to osf when adding models by git annex addurl about trained-models

[satra]

Try replacing the www with dl

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On Fri, Oct 14, 2022, 8:10 PM Hoda Rajaei ***@***.***> wrote: I tried to push a model to osf after adding it with git annex addurl and I got an error. here is what I did: While in the root path of trained_model: mkdir UCL/SynthSeg/2.0.0/conventional/weights git annex addurl --relaxed --file UCL/SynthSeg/2.0.0/conventional/weights/synthseg_2.0.h5 https://www.dropbox.com/s/nu8ap1iicmute3y/synthseg_2.0.h5?dl=1 datalad get UCL/SynthSeg/2.0.0/conventional/weights/synthseg_2.0.h5 datalad push datalad push --to origin I am getting this error: [ERROR ] KeyError('bytesize') (KeyError) and push gets aborted. I tested the downloaded model file with this link and it works. so the model file is OK. — Reply to this email directly, view it on GitHub <#44>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AABM572JDQMRAZI5JYXM6T3WDHY5PANCNFSM6AAAAAARFVKAYE> . You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>

[Hoda1394]

Same situation...

[satra]

Create a clean state and try adding the url without the fast or relaxed flags. Neurostars has an issue posted about this.

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On Sat, Oct 15, 2022, 12:53 AM Hoda Rajaei ***@***.***> wrote: Same situation... — Reply to this email directly, view it on GitHub <#44 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AABM573CMV6DL6TCMH3WEV3WDI2DVANCNFSM6AAAAAARFVKAYE> . You are receiving this because you commented.Message ID: ***@***.***>

[satra]

did this work?

[Hoda1394]

I updated the Datalad and then I was able to push the model to osf but I got an error when I wanted to download it! as I did some search, it seems that I should change the backend for the file after getting it from the web which still did not try.

[hvgazula]

@gaiborjosue Let's discuss this at our next meeting.

[gaiborjosue]

In my case, this was solved using datalad only throughout these steps. Not combining git with datalad push & save.