Bump datasets from 4.5.0 to 4.6.0

[dependabot]

Bumps datasets from 4.5.0 to 4.6.0.

Release notes

Sourced from datasets's releases.

4.6.0

Dataset Features

• Support Image, Video and Audio types in Lance datasets

  • Infer types from lance blobs by @​lhoestq in huggingface/datasets#7966

  >>> from datasets import load_dataset
  >>> ds = load_dataset("lance-format/Openvid-1M", streaming=True, split="train")
  >>> ds.features
  {'video_blob': Video(),
   'video_path': Value('string'),
   'caption': Value('string'),
   'aesthetic_score': Value('float64'),
   'motion_score': Value('float64'),
   'temporal_consistency_score': Value('float64'),
   'camera_motion': Value('string'),
   'frame': Value('int64'),
   'fps': Value('float64'),
   'seconds': Value('float64'),
   'embedding': List(Value('float32'), length=1024)}

• Push to hub now supports Video types

  • push_to_hub() for videos by @​lhoestq in huggingface/datasets#7971

   >>> from datasets import Dataset, Video
  >>> ds = Dataset.from_dict({"video": ["path/to/video.mp4"]})
  >>> ds = ds.cast_column("video", Video())
  >>> ds.push_to_hub("username/my-video-dataset")

• Write image/audio/video blobs as is in parquet (PLAIN) in push_to_hub() by @​lhoestq in huggingface/datasets#7976

  • this enables cross-format Xet deduplication for image/audio/video, e.g. deduplicate videos between Lance, WebDataset, Parquet files and plain video files and make downloads and uploads faster to Hugging Face
  • E.g. if you convert a Lance video dataset to a Parquet video dataset on Hugging Face, the upload will be much faster since videos don't need to be reuploaded. Under the hood, the Xet storage reuses the binary chunks from the videos in Lance format for the videos in Parquet format
  • See more info here: https://huggingface.co/docs/hub/en/xet/deduplication

• Add IterableDataset.reshard() by @​lhoestq in huggingface/datasets#7992

  Reshard the dataset if possible, i.e. split the current shards further into more shards. This increases the number of shards and the resulting dataset has num_shards >= previous_num_shards. Equality may happen if no shard can be split further.

  The resharding mechanism depends on the dataset file format:

  • Parquet: shard per row group instead of per file

... (truncated)

Commits

• c02b863 release: 4.6.0 (#8025)
• bd43ab9 Allow import polars in map() (#8024)
• f428626 Support empty shard in from_generator (#8023)
• fe7353a More IterableDataset.from_x methods and docs and polars.Lazyframe support (#8...
• d58f2cc Fix: make environment variable naming consistent (issue #7998) (#8000)
• 8f566df Bump fsspec upper bound to 2026.2.0 (fixes #7994) (#7995)
• 3495e43 very basic support for more hf urls (#8003)
• 025593f Add IterableDataset.reshard() (#7992)
• 24604d0 Remove pre-release workaround in CI for transformers v5 and `huggingface_hu...
• 6db5f80 Remove unused data files optims (#7985)
• Additional commits viewable in compare view

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[AlexanderDokuchaev]

@copilot modify this branch, bump version of dataset package in all requirements.txt and constraints.txt files

[Copilot]

@AlexanderDokuchaev I've opened a new pull request, #3955, to work on those changes. Once the pull request is ready, I'll request review from you.