Hey 🙂 I had a similar issue today and found this solution:

In my case this codebase was using a .pt filetype which was being picked up and logged as a model even though it was not.

import os
from clearml import Task
from clearml.binding.frameworks import WeightsFileHandler

task = Task.init(
    project_name="task_project",
    task_name="task_name",
    task_type=Task.TaskTypes.training,
)


def filter_out_pt_files(operation_type, model_info):
    is_pt_file = os.path.splitext(model_info.local_model_path)[-1] == ".pt"
    if is_pt_file:
        return None

    return model_info


WeightsFileHandler.add_pre_callback(filter_out_pt_files)

...

If you can identify a patten in the YOLOv8 output files you can probably also filter them out 🙂

If anyone knows a better way, would love to hear about it 🙂

Thank you Tom! Do you add callback to task to filter the files or is that some custom logging code that you created?

I need to add callback for it to filter out anything with .pt

If you added a print there like:

def filter_out_pt_files(operation_type, model_info):
    print(model_info.__dict__)

    return model_info

You can see what is bring picked up. If there is a common path etc you can filter that out