Cool, didn't know it was disabled. This exact reason was why I created a wrapper over ClearML for my use so that people don't ever accidentally talk to demo server

Got the engine running.

curl <serving-engine-ip>:8000/v2/models/keras_mnist/versions/1What’s the serving-engine-ip supposed to be?

Not able to understand what’s really happening in the links

Got it, thanks

Hey SuccessfulKoala55 Like I mentioned, I have a spacy ner model that I need to serve for inference.

One more help - is this something I can pass as task_overrides when creating a pipeline in add_step?

` pipe = PipelineController(
default_execution_queue="minerva-default",
add_pipeline_tags=True,
target_project=pipelines_project,
)

    for step in self.config["steps"]:
        name = self._experiment_name(step)
        pipe.add_step(
            name=name,
            base_task_project=pipelines_project,
            base_task_name=name,
            parents=self._get_parents(step),
            task_overrides...

This is my code, but it’s pretty standard

in the repo whereas the docs are https://allegroai.github.io/clearml-server-helm/

don’t know what’s happening there

I only see published getting preference, not a way to filter only to published

more like testing especially before a pipeline

And other question is clearml-serving ready for serious use?

AgitatedDove14 sounds almost what might be needed, will give it a shot. Thanks, as always 🙂

Something like this - https://aws.amazon.com/blogs/machine-learning/processing-pdf-documents-with-a-human-loop-using-amazon-textract-and-amazon-augmented-ai/

Thanks let me try playing with these!

Thanks that works. Had to use Task.completed() for my version

A channel here would be good too 🙂

AgitatedDove14 - the actual replication failed. When we run a task by cloning and enqueueing, there is a current task even if I am yet to do a Task.init right?

This is so cool!

I am running from noebook and cell has returned

AgitatedDove14 - any thoughts?

As in run a training experiment, then a test/validation experiment to choose best model etc etc and also have a human validate sample results via annotations all as part of a pipeline

just that the task itself is still Running state

Initially thought use_current_task in Dataset.create does it, but that seems to set the DataprocessingTask itself to the current task

Yeah concerns make sense.

The underlying root issue is unnecessary models being added or at least what I think are unnecessary and even happening when you load a model to test.

Do people use ClearML with huggingface transformers? The code is std transformers code.

Will create an issue.

Can you point me at the relevant code?

AlertBlackbird30 - got it running. Few comments:

Nodeport is set by default despite being parameter in values.yml. For example:` webserver:
extraEnvs: []

service:
type: NodePort
port: 80 `2. Ingress was using 8080 for webserver but service was 80
3. Had to change path in ingress to “/*” instead of “/” to get it working for me

CynicalBee90 - on the platform agnostic aspect - dvc does it with the CLI right? It that what made you give a green checkmark for it?

What could those triggers be?