@<1523701087100473344:profile|SuccessfulKoala55> I think I might have made a mistake earlier - but not in the code I posted before. Now, I have the following situation:

• In my training Python process on my notebook I train the custom made model and put it on my harddrive as a zip file. Then I run the code

output_model = OutputModel(task=task, config_dict={...}, name=f"...")
output_model.update_weights(weights_filename=r"C:\path\to\mymodel.zip", is_package=True)

2. I delete the "C:\path\to\mymodel.zip", because it would not be available on my colleagues' computers.

3. In a second process, the model-inference process, I run

mymodel = task.models['output'][-1]
mymodel = mymodel.get_local_copy(extract_archive=True, raise_on_error=True)

and get the error

ValueError: Could not retrieve a local copy of model weights 8ad4db1561474c43b0747f7e69d241a6, failed downloading

I do not have an aws S3 instance or something like that. This is why I would like to store my mymodel.zip file directly on the ClearML Hosted Service. The model is around 2MB large.

How should I proceed?