build(deps): bump the python-minor-patch group across 1 directory with 18 updates

[dependabot]

Bumps the python-minor-patch group with 14 updates in the / directory:

Package	From	To
transformers	5.3.0	5.12.0
huggingface-hub	1.10.2	1.19.0
safetensors	0.7.0	0.8.0
numpy	2.4.4	2.4.6
pandas	3.0.2	3.0.3
matplotlib	3.10.9	3.11.0
tqdm	4.67.3	4.68.2
peft	0.19.0	0.19.1
accelerate	1.13.0	1.14.0
scikit-learn	1.8.0	1.9.0
ruff	0.15.10	0.15.17
pytest	9.0.3	9.1.0
pre-commit	4.5.1	4.6.0
ipykernel	7.2.0	7.3.0

Updates transformers from 5.3.0 to 5.12.0

Release notes

Sourced from transformers's releases.

Release v5.12.0

New Model additions

MiniMax-M3-VL

MiniMax-M3-VL is the vision-language member of the MiniMax-M3 family that pairs a CLIP-style vision tower with 3D rotary position embeddings with the MiniMax-M3 text backbone. It uses a mixed dense/sparse Mixture-of-Experts decoder with SwiGLU-OAI gated experts and a lightning indexer for block-sparse attention. The model processes images through a Conv3d patch embedding system and includes specialized components for efficient multimodal understanding and generation.

Links: Documentation

• Add minimax m3vl (#46600) by @​ArthurZucker in #46600

PP-OCRv6: update documentation and slow tests (#46576)

The official weights for PP-OCRv6 are out: PP-OCRv6 is a lightweight OCR system that combines architectural innovation with data-centric optimization. It redesigns the backbone, detection neck, and recognition neck around a unified MetaFormer-style building block with structural reparameterization. Three model tiers (medium, small, tiny) share the same block primitives, covering deployment scenarios from server to edge.

• PP-OCRv6: update documentation and slow tests (#46576) by @ zhang-prog

Add Parakeet-RNNT (#46331)

ParakeetForRNNT: a Fast Conformer Encoder + an RNN-T (RNN Transducer) decoder

• RNN-T Decoder: Standard neural transducer:
  • LSTM prediction network maintains language context across token predictions.
    • Joint network combines encoder and decoder outputs.
    • Greedy transducer decoding for inference: a blank emission advances the encoder frame by one, a non-blank emission stays on the same frame.

• Add Parakeet-RNNT (#46331) by @​eustlb

Bugfixes and improvements

• [CI] don't export OTELs within the tests (#46602) by @​tarekziade in #46602
• [CI] capture checkers output in OTEL (#46601) by @​tarekziade in #46601
• Lfm2: thread seq_idx through ShortConv for packed/varlen inputs (#46588) by @​ChangyiYang in #46588
• put output_hidden_states into filter_output_hidden_states (#46422) by @​molbap in #46422
• a11 for checkers (#46599) by @​tarekziade in #46599
• Fix stop string matching for byte-fragment tokens (#46530) by @​Incheonkirin in #46530
• [DiffusionGemma] better docs and links (#46569) by @​gante in #46569
• Require trust_remote_code to run a local-directory custom_generate (#46483) by @​LinZiyuu in #46483
• Fix torchaudio version not tied to torch version in docker file (#46594) by @​ydshieh in #46594
• [CI] Enable PR CI for all fork PRs via security gate (#46591) by @​ydshieh in #46591
• [CB] [Minor] Add parameter to tune default compile level (#46533) by @​remi-or in #46533
• Make DiffusionGemma trainable (#46568) by @​kashif in #46568

... (truncated)

Commits

• e0e7504 Revert "fix security issue with allow all kernels"
• 7904f30 fix security issue with allow all kernels
• d77d573 fix kernel path
• f7999c7 v5.12.0
• 4c5d4fd Add minimax m3vl (#46600)
• 5957e6f [CI] capture checkers output in OTEL (#46601)
• 2d68208 Lfm2: thread seq_idx through ShortConv for packed/varlen inputs (#46588)
• 0627d52 put output_hidden_states into filter_output_hidden_states (#46422)
• cd67dbf a11 for checkers (#46599)
• a16a9c7 Fix stop string matching for byte-fragment tokens (#46530)
• Additional commits viewable in compare view

Updates huggingface-hub from 1.10.2 to 1.19.0

Release notes

Sourced from huggingface-hub's releases.

[v1.19.0] Trusted Publishers, hf:// URIs, and expose-ports for Jobs

🔐 Keyless CI/CD auth via OIDC token exchange

CI workflows can now authenticate to the Hub without storing an HF_TOKEN secret, using Trusted Publishers. Set HF_OIDC_RESOURCE to the repo (or username) you want to scope the token to, and huggingface_hub performs the OIDC exchange under the hood — no token, no setup code. GitHub Actions is supported out of the box (with permissions: id-token: write), and other providers can pass a pre-minted ID token via HF_OIDC_ID_TOKEN. Exchanged tokens are short-lived (1 hour), repo-scoped, and cached locally with automatic refresh.

# Publish a model without storing any HF_TOKEN secret
- name: Push the model
  env:
    HF_OIDC_RESOURCE: acme/awesome-model
  run: hf upload acme/awesome-model ./model .

• [Auth] Keyless CI/CD auth via OIDC token exchange by @​hanouticelina in #4326

📚 Documentation: Trusted Publishers

🖥️ hf:// URIs for upload and download

hf upload and hf download now accept an hf:// URI in place of the positional repo ID. The URI encodes repo type, revision, and file path in a single string following the grammar hf://[<TYPE>/]<ID>[@<REVISION>][/<PATH>], so you no longer need separate --repo-type and --revision flags. When a URI is provided, it is the single source of truth — passing --repo-type or --revision on top of it raises an error, and a path in the URI cannot be combined with positional filenames (download) or path_in_repo (upload).

# Download a single file from a dataset at a given revision
hf download hf://datasets/HuggingFaceM4/FineVision@refs/pr/1/data/train.parquet
Download an entire repo
hf download hf://datasets/google/fleurs
Upload a file to a dataset on a specific branch
hf upload hf://datasets/Wauplin/my-cool-dataset@my-branch/data/train.csv ./train.csv

• [CLI] Support hf:// URIs in hf upload and hf download by @​Wauplin in #4297

📚 Documentation: CLI guide — hf:// URIs · Download guide · Upload guide

🚀 Expose job ports through the jobs proxy

Jobs can now expose container ports through the public jobs proxy using --expose <port> (CLI) or expose=[8000] (Python API). Each exposed port is reachable at https://<job_id>--<port>.hf.jobs and requires an HF token with read access to the job's namespace. This works on hf jobs run, hf jobs uv run, and their scheduled variants. Job responses now surface expose_urls on JobStatus.

# Expose a web server running on port 8000
> hf jobs run --expose 8000 python:3.12 python -m http.server 8000
✓ Job started
  id: 6a2aa7cec4f53f9fc5aa4cff
  url: https://huggingface.co/jobs/Wauplin/6a2aa7cec4f53f9fc5aa4cff
Hint: Exposed ports are reachable at (requires an HF token with read access to the job):
  https://6a2aa7cec4f53f9fc5aa4cff--8000.hf.jobs
Serving HTTP on 0.0.0.0 port 8000 (http://0.0.0.0:8000/) ...

... (truncated)

Commits

• b1909eb Release: v1.19.0
• fe27c47 OIDC: Include error_description in HTTP error messages (#4341)
• 68dd701 Release: v1.19.0.rc1
• 934797e Release: v1.19.0.rc0
• 69ef7d7 [Agent] Dynamic agent harness registry (#4325)
• f6b439c [fix] Transient locaion error due to CDN (#4339)
• f1f2c43 Fix ignored-pattern warning grammar in download CLI (#4337)
• 92009d4 [Tests] Add xet/no_xet pytest markers to filter Xet vs non-Xet tests (#4336)
• e3b6d5b [Auth] Keyless CI/CD auth via OIDC token exchange (#4326)
• 8e4ca5c [CI] Remove .github/workflows/python-prerelease.yml (#4335)
• Additional commits viewable in compare view

Updates safetensors from 0.7.0 to 0.8.0

Release notes

Sourced from safetensors's releases.

v0.8.0

News

safetensors joins the PyTorch foundation!

Read more on that: https://huggingface.co/blog/safetensors-joins-pytorch-foundation

What's changed

Safetensors 0.8.0 brings direct to Metal loading on Apple Silicon, GIL-free serialization, broader hardware and dtype coverage, and a stronger Python API.

Breaking

The serialize and serialize_file functions now release the GIL during writes, enabling true multithreaded saves from Python. Their input contract has also changed: tensor metadata is now passed via a TensorSpec class (exported from safetensors) instead of plain dicts, making API more explicit and robust to misinputs. This is a breaking change for anyone calling the low-level serialize / serialize_file API directly; the high-level wrappers (safetensors.torch, safetensors.numpy, safetensors.paddle) are updated internally and their public API is unchanged.

The minimum supported Python version is now 3.10 (was 3.9). Python 3.9 reached end-of-life in October 2025.

TensorIndexer::Narrow now carries a step: NonZeroUsize parameter, so a slice is now start:stop:step. This is a fix as this silent error was hidden behind the Storage::Torch variant which offloaded slicing logic to torch directly.

CI

On the platform side, this release adds Windows ARM64 wheel builds, riscv64 Linux wheels, and CI has been hardened with pinned GitHub Actions SHAs.

Also dropped the anaconda CI we had as there's already an automatic tracker via conda-forge.

New features

• Direct MPS load on Apple Silicon: tensors are directly loaded in an MTLBuffer and handed to the frameworks that support it (only torch atm) via DLPack, skipping needless copies.
• New backend parameter introduced, for the addition of the pread backend. We now support loading files via pread(2) syscall instead of just mmap. Useful for specific archs/platforms.
• get_slice now handles ellipsis [...] and strided slices [:, ::8] wherever safetensors does the slicing itself (pread for any framework, MPS, and mmap outside torch/paddle), which silently dropped the step or rejected ... before.
• MUSA device support for MooreThreads GPUs.
• New dtype support includes float8_e4m3fnuz and float8_e5m2fnuz (AMD FNUZ FP8 formats).
• The reader is now explicitly lenient about leading whitespace in the JSON header, which keeps the door open for future page-aligned writes.

Improvements/perf

• File writes on macOS now use F_NOCACHE for direct I/O, yielding roughly 30% faster save_file on Apple Silicon.
• The packaging dependency has been dropped from the [torch] extra, replaced by a simple hasattr probe for efficiency.

What's Changed

• Add arm64 windows support by @​finnagin in safetensors/safetensors#678
• feat(backend): support musa backend for MooreThreads GPU by @​caizhi-mt in safetensors/safetensors#671
• add gil free serialize_file(serialize_file_threadable) by @​TomQunChao in safetensors/safetensors#679
• refactor: remove outdated comment by @​McPatate in safetensors/safetensors#685
• feat: add direct io write fast path on macos by @​McPatate in safetensors/safetensors#687
• fix: keep dropped reference to tensor moved from gpu to cpu by @​McPatate in safetensors/safetensors#689
• feat: bump torch to 2.4 by @​McPatate in safetensors/safetensors#710
• Contribution guide security by @​LysandreJik in safetensors/safetensors#712

... (truncated)

Changelog

Sourced from safetensors's changelog.

0.8.0-dev.0 → 0.8.0

Update lockfiles again:
cargo check
cd bindings/python && uv lock
</code></pre>
<p>Commit:</p>
<pre><code>Set version to 0.8.0
</code></pre>
<p>The Python version is not set in <code>pyproject.toml</code> directly — maturin reads it from <code>bindings/python/Cargo.toml</code> at build time.</p>
<h3>4. Create the release on GitHub</h3>
<p>Go to the <a href="https://github.com/huggingface/safetensors/releases">GitHub Releases page</a> and draft a new release:</p>
<ul>
<li><strong>Choose the release branch</strong> (e.g. <code>git_v0.8.0</code>)</li>
<li><strong>Create a new tag</strong> on publish: <code>v0.8.0</code></li>
<li><strong>Generate release notes</strong> from the previous tag (e.g. <code>v0.7.0</code>)</li>
<li>Add any notable highlights at the top of the generated notes</li>
</ul>
<p>Structure for manual notes:</p>
<pre lang="markdown"><code>## Breaking changes
- ...
New features

...

Bug fixes

...

Internal / CI

...

</code></pre>

<p>Click <strong>Publish release</strong>. This creates the tag, which triggers the three release workflows.</p>

<h3>5. Monitor the CI</h3>

<p>The tag triggers two workflow runs in the <a href="https://github.com/huggingface/safetensors/actions&quot;&gt;Actions tab</a>:</p>

<ul>

<li><strong>CI</strong> (Python release) — builds wheels for every platform × Python version, uploads to PyPI. Can take up to over 30 minutes.</li>

</ul>

<!-- raw HTML omitted -->

</blockquote>

<p>... (truncated)</p>

</details>

<details>

<summary>Commits</summary>

<ul>

<li><a href="https://github.com/safetensors/safetensors/commit/a406ca3e7a90598be0cd05a50069cb9bf5ef6ba6&quot;&gt;&lt;code&gt;a406ca3&lt;/code&gt;&lt;/a> fix(release): move crates.io to trusted publisher OIDC</li>

<li><a href="https://github.com/safetensors/safetensors/commit/d0368d14c0a417fb2ca2a6627e9513d17f74f9b7&quot;&gt;&lt;code&gt;d0368d1&lt;/code&gt;&lt;/a> feat: <code>0.8.0</code></li>

<li><a href="https://github.com/safetensors/safetensors/commit/5ec3ec14c506d09598df6d96f36cd9a4ea94aafa&quot;&gt;&lt;code&gt;5ec3ec1&lt;/code&gt;&lt;/a> fix(release): move to pypi trusted publisher OIDC (<a href="https://redirect.github.com/huggingface/safetensors/issues/778&quot;&gt;#778&lt;/a&gt;)&lt;/li>

<li><a href="https://github.com/safetensors/safetensors/commit/e37dc536ce598ef1d71a9ad712987571f2f05808&quot;&gt;&lt;code&gt;e37dc53&lt;/code&gt;&lt;/a> feat: bump main to <code>0.9.0-dev.0</code> (<a href="https://redirect.github.com/huggingface/safetensors/issues/777&quot;&gt;#777&lt;/a&gt;)&lt;/li>

<li><a href="https://github.com/safetensors/safetensors/commit/6e32aa7b029d323238233110c1cdecae22cbe564&quot;&gt;&lt;code&gt;6e32aa7&lt;/code&gt;&lt;/a> refactor: replace <code>_host_alias_storage</code> w/ <code>MTLBuffer</code> (<a href="https://redirect.github.com/huggingface/safetensors/issues/767&quot;&gt;#767&lt;/a&gt;)&lt;/li>

<li><a href="https://github.com/safetensors/safetensors/commit/24b0b2857fef49be734b9ab72ce97c09bb25f5b9&quot;&gt;&lt;code&gt;24b0b28&lt;/code&gt;&lt;/a> fix: write to tempfile + rename to preserve mmap source (<a href="https://redirect.github.com/huggingface/safetensors/issues/764&quot;&gt;#764&lt;/a&gt;)&lt;/li>

<li><a href="https://github.com/safetensors/safetensors/commit/73132135947275c5dda135438e4c2e4bd70a2b10&quot;&gt;&lt;code&gt;7313213&lt;/code&gt;&lt;/a> Update free-threading tests for Python 3.14 (<a href="https://redirect.github.com/huggingface/safetensors/issues/699&quot;&gt;#699&lt;/a&gt;)&lt;/li>

<li><a href="https://github.com/safetensors/safetensors/commit/e9091e13ec359e9e5b8b45413fcbe340444dde1c&quot;&gt;&lt;code&gt;e9091e1&lt;/code&gt;&lt;/a> feat: add <code>backend</code> with pread file (<a href="https://redirect.github.com/huggingface/safetensors/issues/760&quot;&gt;#760&lt;/a&gt;)&lt;/li>

<li><a href="https://github.com/safetensors/safetensors/commit/1b0fe9c6acf3ac2ec7f4a0fd13bccfc0b65ce765&quot;&gt;&lt;code&gt;1b0fe9c&lt;/code&gt;&lt;/a> fix(ci): security audit slack message format (<a href="https://redirect.github.com/huggingface/safetensors/issues/757&quot;&gt;#757&lt;/a&gt;)&lt;/li>

<li><a href="https://github.com/safetensors/safetensors/commit/7efac22872a53ae3b30a15f8e786404322f10458&quot;&gt;&lt;code&gt;7efac22&lt;/code&gt;&lt;/a> [MPS] Fast load of the tensors (<a href="https://redirect.github.com/huggingface/safetensors/issues/756&quot;&gt;#756&lt;/a&gt;)&lt;/li>

<li>Additional commits viewable in <a href="https://github.com/huggingface/safetensors/compare/v0.7.0...v0.8.0&quot;&gt;compare view</a></li>

</ul>

</details>
<br />

Updates numpy from 2.4.4 to 2.4.6

Release notes
Sourced from numpy's releases.

v2.4.6 (May 18, 2026)
NumPy 2.4.6 Release Notes
NumPy 2.4.6 is a quick release that fixes a regression discovered in the 2.4.5
release.
This release supports Python versions 3.11-3.14
Contributors
A total of 4 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.

!EarlMilktea
Charles Harris
Sebastian Berg
Warren Weckesser

Pull requests merged
A total of 4 pull requests were merged for this release.

#31444: MAINT: Prepare 2.4.x for further development
#31453: BUG: Fix regression in arr.conj()
#31459: BUG: np.linalg.svd(..., hermitian=True) returns non-unitary...
#31460: BUG: Don't call INCREF/DECREF on descr in NpyStringAcquireAllocator...

v2.4.5 (May 15, 2026)
NumPy 2.4.5 Release Notes
NumPy 2.4.5 is a patch release that fixes bugs discovered after the 2.4.4
release, has some typing improvements, and maintains infrastructure.
This release supports Python versions 3.11-3.14
Contributors
A total of 17 people contributed to this release. People with a "+" by their
names contributed a patch for the first time.

Aleksei Nikiforov
Anarion Zuo +
Ankit Ahlawat
Breno Favaretto +
Charles Harris
Igor Krivenko +
Ijtihed Kilani +
Joren Hammudoglu
Maarten Baert +



... (truncated)


Commits

b832a09 Merge pull request #31462 from charris/prepare-2.4.6
57cc147 REL: Prepare for the NumPy 2.4.6 release
0c72b0b Merge pull request #31459 from charris/backport-31347
9778d26 BUG: core: Don't call INCREF/DECREF on descr in NpyStringAcquireAllocator. (#...
e0e3876 BUG: core: Don't call INCREF/DECREF on descr in NpyStringAcquireAllocator. (#...
d1bffeb BUG: np.linalg.svd(..., hermitian=True) returns non-unitary vh (#31347)
8d8d7e5 Merge pull request #31453 from seberg/issue-31452
bddaab7 BUG: Fix regression in arr.conj()
37a1ecc Merge pull request #31444 from charris/begin-2.4.6
3c0e043 MAINT: Prepare 2.4.x for further development
Additional commits viewable in compare view




Updates pandas from 3.0.2 to 3.0.3

Release notes
Sourced from pandas's releases.

pandas 3.0.3
We are pleased to announce the release of pandas 3.0.3.
This is a patch release in the 3.0.x series and includes some regression fixes and bug fixes. We recommend that all users of the 3.0.x series upgrade to this version.
See the full whatsnew for a list of all the changes.
Pandas 3.0 supports Python 3.11 and higher.
The release can be installed from PyPI:
python -m pip install --upgrade pandas==3.0.*

Or from conda-forge
conda install -c conda-forge pandas=3.0

Please report any issues with the release on the pandas issue tracker.
Thanks to all the contributors who made this release possible.



Commits

72f2fea RLS: 3.0.3 (#65590)
2897590 Backport PR #65436 on branch 3.0.x (Account for privatization of matplotlib `...
49894b5 Backport PR #65499 on branch 3.0.x (BUG: fix check if pyarrow is installed in...
1c6d1e3 [backport 3.0.x] PERF: remove special casing for zoneinfo in tz_localize_to_u...
2a54711 Backport PR #64379 on branch 3.0.x (PERF: improve performance with ZoneInfo t...
036bb7c Backport PR #65482 on branch 3.0.x (PERF: don't call unique on dtypes for che...
bf4c182 Backport PR #65410 on branch 3.0.x (TST: also convert str index to object in ...
dd02d75 [backport 3.0.x] BUG: keep fsspec OpenFile alive for chained URL reads (#6547...
aef3d0f [backport 3.0.x] CI: lowercase types-pymysql/types-pyyaml to fix mamba 2.6.0 ...
bb8e248 Backport PR #65399 on branch 3.0.x (DOC: fix source link for classes in the r...
Additional commits viewable in compare view




Updates matplotlib from 3.10.9 to 3.11.0

Release notes
Sourced from matplotlib's releases.

REL: v3.11.0
The largest change within this release is a complete overhaul of text and font processing. Through the use of libraqm, HarfBuzz, SheenBidi, and an updated release of FreeType, all text should now support modern font features, enabling full internationalization in all languages. Not all features of these libraries are supported yet, but we expect this work to enable further improvements in an easier manner.
Outside of text handling, there are several improvements to 3D Axes, performance, new accessible colour sequences, flexible figure management, and more. See the release notes for more information.
REL: v3.11.0rc2
This is the second release candidate for the meso release 3.11.0.
This release candidate fixes some problems with downstream packages, removes some missed deprecations, and corrects some additional minor bugs.
REL: v3.11.0rc1
After an extended development stretch, we are pleased to announce the first release candidate of Matplotlib 3.11.0.
The largest change within this release is a complete overhaul of text and font processing. Through the use of libraqm, HarfBuzz, SheenBidi, and an updated release of FreeType, all text should now support modern font features, enabling full internationalization in all languages. Not all features of these libraries are supported yet, but we expect this work to enable further improvements in an easier manner. Due to the update to the font rendering stack, we cannot guarantee that text will be bit-for-bit perfect with previous releases, so if you are using Matplotlib for testing, it may be necessary to introduce/raise a tolerance within your tests.
Outside of text handling, there are several improvements to 3D Axes, performance, new accessible colour sequences, flexible figure management, and more. Final release notes are still being curated, but you may browse the list of new features, API changes, and all issues/pull requests on the milestone.
As a note for downstream packagers, the font libraries have only been tested against the versions bundled with the wheels. It may be possible to expand the range of requirements, or that a requirement is too broad. Please report any issues you have building against external dependencies.



Commits

69c7534 REL: v3.11.0
b7d912b DOC: Set 3.11 as preferred stable release
7c3d502 Update Security Policy for 3.11
964e73d DOC: Prepare GitHub stats for 3.11 final
bfa2633 Bump font manager version to final release
d0603b2 Merge pull request #31873 from meeseeksmachine/auto-backport-of-pr-31706-on-v...
edf5ebc Backport PR #31706: Fix clabel manual index
c0e80b7 Merge pull request #31872 from meeseeksmachine/auto-backport-of-pr-31868-on-v...
2a14854 Backport PR #31868: DOC: Move errorbar examples to the statistics sections
ea43d96 Merge pull request #31871 from meeseeksmachine/auto-backport-of-pr-31870-on-v...
Additional commits viewable in compare view




Updates tqdm from 4.67.3 to 4.68.2

Release notes
Sourced from tqdm's releases.

tqdm v4.68.2 stable

revert accidental change to ascii default (fixes #1760)

UnicodeEncodeError: 'charmap' codec can't encode characters in position 6-7: character maps to <undefined> can be fixed by installing tqdm!=4.68.0,!=4.68.1


misc docs updates

fix links
replace stray rst -> md syntax
consistent "progress bar" terminology (#1737)


tests: fix coverage (fixes #1760)

tqdm v4.68.1 stable

set name of monitor thread (#1669, #1752 <- #1435)
fix monitor thread atexit deadlock (#1751 <- #528, #627, #1435, #1564)
docs: minor copyediting

tqdm v4.68.0 stable

utils: simplify terminal size detection (#1760)
contrib

itertools (#1760)

add chain, permutations, combinations, combinations_with_replacement, batched
add product(repeat=1) keyword argument (#1428)


fix discord, telegram error handling
fix discord, slack, telegram format for total=None


soft-deprecate tqdm.utils.envwrap -> envwrap
benchmarks: fix asv
misc linting
misc framework updates

CI: migrate manual job to pre-commit.ci
bump workflow actions & pre-commit hooks






Commits

4b33952 revert accidental change to tqdm(ascii) default
b10848f docs: fix links
85b62dd docs: replace stray rst -> md
d2fb04a docs: mention OpenAI sponsorship
85940f9 docs: consistent progress bar terminology
9dbb36b tests: fix coverage
67cf355 Merge pull request #1751 from jaltmayerpizzorno/fix-atexit-monitor-deadlock
cfa4a85 minor docstring updates
f83290c Fix TMonitor deadlock at interpreter shutdown
59029c3 Set name for tqdm monitor thread (#1752)
Additional commits viewable in compare view




Updates peft from 0.19.0 to 0.19.1

Release notes
Sourced from peft's releases.

v0.19.1
A small patch release containing these fixes:

#3161
#3165

Full Changelog: https://github.com/huggingface/peft/compare/v0.19.0...v0.19.1



Commits

ba6a190 Patch release 0.19.1 (#3168)
See full diff in compare view




Updates accelerate from 1.13.0 to 1.14.0

Release notes
Sourced from accelerate's releases.

v1.14.0: AMD ROCm support, FSDP2 hardening
FSDP2 Improvements
This release brings a large batch of FSDP2 fixes and quality-of-life improvements: correct dtype handling on load, sharding of embeddings/norms, QLoRA crash prevention, and a more robust auto-wrap policy.

Fsdp2 fully_shard embedding and norm by @​SunMarc in #4015
Fix fsdp2 load full state dict dtype mismatch by @​SunMarc in #4021
Fix region compilation fsdpv2 by @​SunMarc in #4022
[FSDP2] Cast model to uniform dtype before fully_shard to fix mixed-dtype AssertionError by @​roycho96 in #3985
[FSDP2] Auto-exclude non-floating frozen Params4bit from fully_shard to prevent QLoRA crash by @​roycho96 in #3987
fix(FSDP2): auto-wrap policy ignoring _no_split_modules fallback by @​JohnGiorgi in #3999
fix: use key-based matching in fsdp2_load_full_state_dict by @​roycho96 in #3982
fix: add missing model_has_params4bit guard to fsdp2_load_full_state_dict call by @​roycho96 in #3981
Fix to-fsdp2: drop REMOVED / NOT_YET_IMPLEMENTED FSDP1 keys instead of leaking them by @​lollinng in #4065
Prevent double-wrapping models in prepare_model() by @​joshuaswanson in #3977

AMD ROCm support
Accelerate now works end-to-end on AMD ROCm devices. Thanks @​Abdennacer-Badaoui!

Make accelerate work end-to-end on AMD ROCm by @​Abdennacer-Badaoui in #4025

Neuron
Further Neuron improvements to reduce recompilation and cover missing device cases.

Add padded allgather and broadcast for Neuron devices to reduce recompilation by @​czkkkkkk in #4000
fix: add missing neuron device case by @​michaelbenayoun in #4042

Quantization & Offloading
We improved offloading support for quantized models, including Torchao, int8, and tied-weight handling.

Torchao offload by @​SunMarc in #3973
Fix int8 offload hook detachment statistics restoration by @​jiqing-feng in #4044
Fix keep_in_fp32_modules not working for tied weights in load_and_quantize_model by @​jiqing-feng in #4043
Fix dtype_byte_size for FP8 fnuz / e8m0fnu dtypes by @​lollinng in #4063

Data Loading

Feat: Support dynamic batch size in BatchSamplerShard with even_batches by @​yuxinyuan in #3969
Fix iterable dataset sharding condition when n_shards == num_processes by @​SunMarc in #3958
Fix implicit padding in split_between_processes when apply_padding=False and num_samples < num_processes by @​3manifold in #4052

Minor fixes

[DeepSpeed] allow kernels flash-attn in SP by @​kashif in #3959
Fix: Conditionally import torch.distributed.algorithms.join in accelerator.py by @​0xDELUXA in #3962
Fix is_hf_initialized attribute by @​SunMarc in #3976
feat(utils): add max reduction type by @​imstevenpmwork in #4027



... (truncated)


Commits

beb0672 Release: v1.14.0
a5cb37c Fix all tests (#4072)
14d7cdc Support dynamic batch size in BatchSamplerShard with even_batches (#3969)
77eb5cf fix(tracker): guard init_trackers and log against None kwargs (#4026)
379c8e0 fix(security): remediate workflow vulnerability in .github/workflows/build-do...
61e6420 Fix to-fsdp2: actually drop REMOVED / NOT_YET_IMPLEMENTED FSDP1 keys (#4065)
b120c1f tests: Gracefully handle missing set_device for mps (#4028)
418015a test: add regression test for no_split_module_classes accepting set type (#4048)
3f1acf8 Bump the actions group with 8 updates (#4068)
a2e5292 docs: add aggregate profiler memory example (#4054)
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Updates scikit-learn from 1.8.0 to 1.9.0

Release notes
Sourced from scikit-learn's releases.

Scikit-learn 1.9.0
We're happy to announce the 1.9.0 release.
You can read the release highlights under https://scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_9_0.html and the long version of the change log under https://scikit-learn.org/stable/whats_new/v1.9.html
This release adds narwhals as a new dependency that will help to improve dataframe interoperability across the project.
This version supports Python versions 3.11 to 3.14.
You can upgrade with pip as usual:
pip install -U scikit-learn

The conda-forge builds can be installed using:
conda install -c conda-forge scikit-learn




Commits

77def0e trigger wheel builder [cd build]
ee7c0b0 generate changelog
3d7fb04 bump version
8954e7b DOC Release highlights for 1.9 (#34147)
73a3eab Fix: Array-API - avoid failing for numpy fit + predict with sparse or array-l...
8839aae DOC Thread-safety requirement for open_listener message consumer callback (#3...
4d2476a DOC Refactor array API docs page (#34054)
f9f812f :lock: :robot: CI Update lock files for scipy-dev CI build(s) :lock: :robot: ...
d779dc3 :lock: :robot: CI Update lock files for free-threaded CI build(s) :lock: :rob...
6a03cf0 :lock: :robot: CI Update lock files for array-api CI build(s) :lock: :robot: ...
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Updates wandb from 0.26.1 to 0.25.0

Changelog
Sourced from wandb's changelog.

[0.26.1] - 2026-04-23
Added

Api methods returning artifacts, registries, automations, and related paginators now accept an optional start argument to resume iteration from a saved cursor (@​tonyyli-wandb in wandb/wandb#11651)
The stop_fn setting to customize how a run is stopped (@​timoffex in wandb/wandb#11773)

Allows overriding the default of sending a SIGINT to the Python process



Changed

Unified keyboard navigation in W&B LEET TUI (wandb beta leet command): wasd and arrow keys are now interchangeable within each focused pane (chart focus in grids, item/page nav in lists), and Home/End/PgUp/PgDn work universally; the media pane retains its deliberate split where arrows scrub and wasd selects tiles (@​dmitryduev in wandb/wandb#11756)

Fixed

Made wandb.init(id=run_id, reinit="create_new") raise an error when another run in the same script with the same run_id is still running (@​timoffex in wandb/wandb#11759)
wandb.Api no longer raises an error for some api operations when offline mode is enabled via the WANDB_MODE environment variable or the mode setting. (@​jacobromero in wandb/wandb#11762)

[0.26.0] - 2026-04-13
Notable Changes
This version drops compatibility with server versions older than 0.63.0 (for Dedicated Cloud and Self-Managed W&B deployments).
Added

wandb beta core start|stop commands to run a detached wandb-core service and reuse it across multiple processes via the WANDB_SERVICE env var (@​dmitryduev in wandb/wandb#11418)
Run filtering by metadata in multi-run workspace mode in W&B LEET TUI (wandb beta leet command, activate with f) (@​dmitryduev in wandb/wandb#11497 and wandb/wandb#11534)
Run overview displays tags and notes in W&B LEET TUI (wandb beta leet command) (@​dmitryduev in wandb/wandb#11523)
Per-chart log-scale (Y-axis) support in W&B LEET TUI (wandb beta leet command, toggle on a selected chart with y) (@​dmitryduev in wandb/wandb#11537)
Standalone system monitor mode in W&B LEET TUI (wandb beta leet symon command) (@​dmitryduev in wandb/wandb#11559)
Bucketed heatmap chart mode for system metrics expressed as percentages (e.g. GPU utilization) in W&B LEET TUI (wandb beta leet command, cycle chart mode on a selected chart with y) (Description has been truncated

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