Also going off this 🙂

The GCP image and Helm chart for ClearML Server maybe slightly delayed for purely man-power reasons.

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

I used .update_weights(path) with path being the model dir containing the model.py annd the config.pbtxt. Should I use update_weights_package ?

Got it thanks TimelyPenguin76 .

It’s a bit difficult to figure out the exact key. Will try this to see if it works

From code perspective what changes?

Will try it out. Pretty impressed 🙂

“notebook as a service” right

AgitatedDove14 - yeah wanted to see what’s happening before disabling as I wasn’t sure if this is what’s expected.

Thanks AgitatedDove14 - is the datasets feature pretty new?

Without some sort of automation on top feels a bit fragile

Sagemaker will make that easy, especially if I have sagemaker as the long tail choice. Granted at a higher cost

Yeah mostly. With k8s glue going, want to finally look at clearml-session and how people are using it.

Is this this the issue?

https://github.com/pypa/pip/issues/8413

This is the command that is running:

` ['docker', 'run', '-t', '-e', 'NVIDIA_VISIBLE_DEVICES=none', '-e', 'CLEARML_WORKER_ID=clearml-services:service:c606029d77784c69a30edfdf4ba291a5', '-e', 'CLEARML_DOCKER_IMAGE=', '-v', '/tmp/.clearml_agent.72r6h9pl.cfg:/root/clearml.conf', '-v', '/root/.clearml/apt-cache:/var/cache/apt/archives', '-v', '/root/.clearml/pip-cache:/root/.cache/pip', '-v', '/root/.clearml/pip-download-cache:/root/.clearml/pip-download-cache', '-v', '/root/.clearml/cache:/clea...

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

So packages have to be installed and not just be mentioned in requirements / imported?

Thanks for the fast responses as usual AgitatedDove14 🙂

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

Thanks

Can I disable this cache?

Ok got it, thanks

In params:

parameter_override={'General/dataset_urlWhat’s the General for?

Ok the doc needs fix

yeah meant this, within clearml.conf:

logging {} sdk {}

Seems like usual? https://github.com/thoughtworks/mlops-platforms#contributions

AgitatedDove14 - on a similar note, using this is it possible to add to requirements of task with task_overrides?

Does a pipeline step behave differently?

Something like the Gitlab Kubernetes Executor could work well.

AgitatedDove14 - are there cases when it tries to skip steps?