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Unable to Control Deployed Model #11

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wbond opened this issue Oct 18, 2024 · 3 comments
Open

Unable to Control Deployed Model #11

wbond opened this issue Oct 18, 2024 · 3 comments
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enhancement New feature or request

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@wbond
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wbond commented Oct 18, 2024

Describe the bug
There are no controls for selecting a deployed model.

To Reproduce
Steps to reproduce the behavior:

  1. Click on an older model …
  2. No option to deploy or select

Also, there is no UI to select the default public model other than deleting all custom models.

Expected behavior
It should be possible to select a previously trained model. It should also be possible to select the public model.

It should not be necessary to delete models to change what is deployed.

Screenshots
CleanShot 2024-10-18 at 09 55 56@2x
CleanShot 2024-10-18 at 09 56 10@2x

Additional context
Add any other context about the problem here.

@justincampbell
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@wbond Thanks for the feedback! While I don't have a timeline yet, we're exploring a few solutions for this now.

@justincampbell justincampbell self-assigned this Oct 18, 2024
@justincampbell justincampbell added the enhancement New feature or request label Oct 18, 2024
@wbond
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wbond commented Oct 30, 2024

We are currently running a controlled experiment on a model we’ve trained, but need to start the process of trying to train a custom model on a larger corpus of repositories at the same time. We can’t have the newer trained model automatically deploy since it will affect our running experiment.

Do you have any way we can accomplish these things today?

cc @thejoebourneidentity

@thejoebourneidentity
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Unfortunately we do not have that at this exact moment, but roll-out management is something we are actively designing and intended to ship ASAP!

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