Hi @<1523701070390366208:profile|CostlyOstrich36>
I did something like this:

data = {"index": ["<a href=

>12345</a>"], y:[1],...}
df = pd.DataFrame(data)
clearml_logger.report_table(title, series, iteration, df)

Hi @<1523701070390366208:profile|CostlyOstrich36> how do I utilize the ‘presentation’:‘markdown’ solution you mentioned in conjunction with logger.report_table? Is it possible?

It was probably just a network issue on my end. Works with a larger delay than I expected.

I redeployed the latest versions and the button appears now
CLEARML_SERVER_VERSION=1.17.0
CLEARML_SERVER_BUILD=542

Hi @<1523701070390366208:profile|CostlyOstrich36>
For example if I want to push a task to a remote queue and have the task's name automatically be inferred from one of the configuration files. My use case is in cross validation training, the task name should include the model_name and the split_id

Hi @<1523701070390366208:profile|CostlyOstrich36> , I deployed using the latest allegroai/clearml image. When I execute /usr/bin/env in the container I get:
CLEARML_SERVER_VERSION=1.16.2
CLEARML_SERVER_BUILD=502

When using clearml-agent daemon --stop will it interrupt the running tasks or wait for the running task to finish and then stop the daemon?

Hi, I got the same issue.

Thanks

Hi @<1523701070390366208:profile|CostlyOstrich36> I have the same issue. I archived then deleted an experiment and the debug samples do not get deleted from the self-hosted fileserver. also no logs that I can find indicate an error.

When you say clearml-serving you mean the CLI? Or the server also?