Add quickstart for pytorch flavor

[chenmoneygithub]

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pip install git+https://github.com/mlflow/mlflow.git@refs/pull/10737/merge

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Related Issues/PRs

#xxx

What changes are proposed in this pull request?

Add a quickstart guide on pytorch flavor.

How is this PR tested?

• Existing unit/integration tests
• New unit/integration tests
• Manual tests

Does this PR require documentation update?

• No. You can skip the rest of this section.
• Yes. I've updated:
  • Examples
  • API references
  • Instructions

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• area/artifacts: Artifact stores and artifact logging
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• area/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrations
• area/docs: MLflow documentation pages
• area/examples: Example code
• area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• area/models: MLmodel format, model serialization/deserialization, flavors
• area/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templates
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• area/scoring: MLflow Model server, model deployment tools, Spark UDFs
• area/server-infra: MLflow Tracking server backend
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• area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
• area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
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• area/windows: Windows support

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• language/java: Java APIs and clients
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• rn/feature - A new user-facing feature worth mentioning in the release notes
• rn/bug-fix - A user-facing bug fix worth mentioning in the release notes
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[BenWilson2]

We can replace this entire block with the page reference here: https://www.mlflow.org/docs/latest/getting-started/running-notebooks/index.html

[chenmoneygithub]

Personally I really like an integrated experience while reading through guides/tutorials, which means the guide/tutorial is the only doc I need to read to get the work done. If it is a ipython notebook, I should be able to click "run all" and wait for the result (filling some prompted info is required tho, like credentials or so).

[jessechancy]

LGTM! Just some small nits

[jessechancy]

Should we say FashionMnist here since Mnist is a different dataset

[chenmoneygithub]

good catch!