StaleButterfly40 , it looks like there might be a good solution for your request. In the previous link I provided, there is a parameter ' continue_last_task' that should work for you 🙂

If it interests you this seems to work
last_task = Task.get_task(project_name="playground-sandbox", task_name='foo2') task = Task.init(project_name="playground-sandbox", task_name='foo2', continue_last_task=last_task.id if last_task else None)

CostlyOstrich36 Thanks!
But it seems like this only works if I am running both times from the same machine because clearml is not checking if task exists in server - it is checking if it is in cache_dir

StaleButterfly40 Hi!
You could clone the original task and edit the input model of the new task as the output model of the previous task 🙂

StaleButterfly40 , alternatively you could use auto_connect_frameworks=False
https://clear.ml/docs/latest/docs/references/sdk/task#taskinit
So torch.save won't automatically save the model, however, you will not get the scalars/metrics automatically as well.

I want everything to appear in the same experiment (e.g scalar metrics)