chore(deps): bump datasets from 4.7.0 to 4.8.4 in /cmd/runtimes/deepspeed

[dependabot]

Bumps datasets from 4.7.0 to 4.8.4.

Release notes

Sourced from datasets's releases.

4.8.4

What's Changed

• Support latest torchvision by @​lhoestq in huggingface/datasets#8087
• fix regression when loading JSON with one file = one object by @​lhoestq in huggingface/datasets#8086

Full Changelog: huggingface/datasets@4.8.3...4.8.4

4.8.3

What's Changed

• Fix split_dataset_by_node step by @​lhoestq in huggingface/datasets#8081
• Fix docstring of Json.cast_storage by @​albertvillanova in huggingface/datasets#8080

Full Changelog: huggingface/datasets@4.8.2...4.8.3

4.8.2

What's Changed

• Json type for empty struct by @​lhoestq in huggingface/datasets#8074

Full Changelog: huggingface/datasets@4.8.1...4.8.2

4.8.1

What's Changed

• Fix formatted iter arrow double yield by @​HaukurPall in huggingface/datasets#8063

Full Changelog: huggingface/datasets@4.8.0...4.8.1

4.8.0

Dataset Features

• Read (and write) from HF Storage Buckets: load raw data, process and save to Dataset Repos by @​lhoestq in huggingface/datasets#8064

  from datasets import load_dataset
  # load raw data from a Storage Bucket on HF
  ds = load_dataset("buckets/username/data-bucket", data_files=["*.jsonl"])
  # or manually, using hf:// paths
  ds = load_dataset("json", data_files=["hf://buckets/username/data-bucket/*.jsonl"])
  # process, filter
  ds = ds.map(...).filter(...)
  # publish the AI-ready dataset
  ds.push_to_hub("username/my-dataset-ready-for-training")

  This also fixes multiprocessed push_to_hub on macos that was causing segfault (now it uses spawn instead of fork). And it bumps dill and multiprocess versions to support python 3.14

• Datasets streaming iterable packaged improvements and fixes by @​Michael-RDev in huggingface/datasets#8068

  • added max_shard_size to IterableDataset.push_to_hub (but requires iterating twice to know the full dataset twice - improvements are welcome)

... (truncated)

Commits

• a0ce369 release: 4.8.4 (#8088)
• 0856825 fix regression when loading JSON with one file = one object (#8086)
• 6ca75d0 Support latest torchvision (#8087)
• 4a0c9c9 set dev version (#8083)
• d4942e2 Release 4.8.3 (#8082)
• 1b31309 Fix split_dataset_by_node step (#8081)
• 4a4813f Fix docstring of Json.cast_storage (#8080)
• 68294ab set dev version (#8077)
• 2c46ab1 release 4.8.2 (#8076)
• 97ba494 Json type for empty struct (#8074)
• Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

---

Dependabot commands and options

You can trigger Dependabot actions by commenting on this PR:

• @dependabot rebase will rebase this PR
• @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
• @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
• @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
• @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)

[google-oss-prow]

[APPROVALNOTIFIER] This PR is NOT APPROVED

This pull-request has been approved by:
Once this PR has been reviewed and has the lgtm label, please assign tenzen-y for approval. For more information see the Kubernetes Code Review Process.

The full list of commands accepted by this bot can be found here.

Details

Needs approval from an approver in each of these files:

• OWNERS

Approvers can indicate their approval by writing /approve in a comment
Approvers can cancel approval by writing /approve cancel in a comment

[github-actions]

🎉 Welcome to the Kubeflow Trainer! 🎉

Thanks for opening your first PR! We're happy to have you as part of our community 🚀

Here's what happens next:

• If you haven't already, please check out our Contributing Guide for repo-specific guidelines and the Kubeflow Contributor Guide for general community standards.
• Our team will review your PR soon! cc @kubeflow/kubeflow-trainer-team

Join the community:

• Slack: Join our #kubeflow-trainer Slack channel.
• Meetings: Attend the Kubeflow AutoML and Training Working Group bi-weekly meetings.

Feel free to ask questions in the comments if you need any help or clarification!
Thanks again for contributing to Kubeflow! 🙏