Hi @<1543766544847212544:profile|SorePelican79> ! You could use the following workaround:

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


def filter_callback(
    callback_type: WeightsFileHandler.CallbackType,
    model_info: WeightsFileHandler.ModelInfo,
):
    print(model_info.__dict__)
    if (
        callback_type == WeightsFileHandler.CallbackType.save
        and "filter_out.pt" in model_info.local_model_path
    ):
        return None
    return model_info


if __name__ == "__main__":
    Task.init(project_name="example", task_name="filter out")
    WeightsFileHandler.add_pre_callback(filter_callback)
    filter_out_model = torch.nn.Module()
    dont_filter_out_model = torch.nn.Module()
    torch.save(filter_out_model, "filter_out.pt")
    torch.save(dont_filter_out_model, "dont_filter_out_model.pt")

As you can see, you can use WeightsFileHandler after the task has been initialized