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:arrow_up: dep-bump(deps): Bump the dependency-packages group across 1 directory with 2 updates

Open dependabot[bot] opened this issue 11 months ago • 0 comments

Bumps the dependency-packages group with 2 updates in the / directory: datasets and transformers.

Updates datasets from 3.2.0 to 3.3.2

Release notes

Sourced from datasets's releases.

3.3.2

Bug fixes

Other general improvements

New Contributors

Full Changelog: https://github.com/huggingface/datasets/compare/3.3.1...3.3.2

3.3.1

Bug fixes

Full Changelog: https://github.com/huggingface/datasets/compare/3.3.0...3.3.1

3.3.0

Dataset Features

  • Support async functions in map() by @​lhoestq in huggingface/datasets#7384

    • Especially useful to download content like images or call inference APIs
    prompt = "Answer the following question: {question}. You should think step by step."
async def ask_llm(example):
    return await query_model(prompt.format(question=example["question"]))
ds = ds.map(ask_llm)

  • Add repeat method to datasets by @​alex-hh in huggingface/datasets#7198

    ds = ds.repeat(10)

  • Support faster processing using pandas or polars functions in IterableDataset.map() by @​lhoestq in huggingface/datasets#7370

    • Add support for "pandas" and "polars" formats in IterableDatasets
    • This enables optimized data processing using pandas or polars functions with zero-copy, e.g.
    ds = load_dataset("ServiceNow-AI/R1-Distill-SFT", "v0", split="train", streaming=True)
ds = ds.with_format("polars")
expr = pl.col("solution").str.extract("boxed\\{(.*)\\}").alias("value_solution")
ds = ds.map(lambda df: df.with_columns(expr), batched=True)

  • Apply formatting after iter_arrow to speed up format -> map, filter for iterable datasets by @​alex-hh in huggingface/datasets#7207

... (truncated)

Commits

Updates transformers from 4.48.0 to 4.49.0

Release notes

Sourced from transformers's releases.

Patch release v4.48.3

This ends the python3.9 issues mostly!

For some very niche cases, the new rope embedding introduced device failures

Num items in batch

  • Fix model kwargs (#35875) by @​muellerzr: this is long due, sorry that it took so long. Some models were not compatible with the num_items_in_batch

Finally the fix to Gemma2 is propagated to paligemma2!

Patch release v4.48.2

Sorry because the fixes for num_items_in_batches are not done yet 😓 To follow along see this PR, a new patch will be available soon!

Now, we mostly had BC issue with python version 3.9:

Then we had a small regression for DBRX saving:

Finally we have a fix for gemma and the hybrid attention architectures:

Miscellaneous:

Patch release v4.48.1

Yet again we are dawned with a gradient accumulation fix! There is also a refactoring of the attention that let a small typo in, we made sure PHI is no longer broken!

Moonshine had a small issue when wrapping generate so we removed that!

🤗

Commits

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dependabot[bot] avatar Feb 24 '25 20:02 dependabot[bot]