rstudio / rstudio/vetiver-python
feat: VetiverModel.from_mlflow(...)
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- Dominant language
- Python
- Stars
- 71
- Forks
- 20
- PR merge metrics
- No merged PRs in 30d
Description
For people either transitioning away from mlflow or just wanting a common interface to easily deploy model endpoints, it would be beneficial to have a helper that knows how to pull a registered model, model-version, or set of model versions into a Vetiver model pin and then able to be deployed to Connect, docker, etc.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by investigating the proposed VetiverModel.from_mlflow(...) entry point and how Vetiver currently represents model pins and deployment targets. Clarify support for registered models, individual model versions, and sets of versions, then verify that the resulting model can be deployed to Connect and Docker as described.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100