build(deps): bump the python-minor-patch group across 1 directory with 19 updates

[dependabot]

Bumps the python-minor-patch group with 15 updates in the / directory:

Package	From	To
transformers	5.3.0	5.12.1
huggingface-hub	1.10.2	1.20.1
safetensors	0.7.0	0.8.0
numpy	2.4.4	2.5.0
pandas	3.0.2	3.0.3
matplotlib	3.10.9	3.11.0
tqdm	4.67.3	4.68.3
peft	0.19.0	0.19.1
accelerate	1.13.0	1.14.0
scikit-learn	1.8.0	1.9.0
scipy	1.17.1	1.18.0
ruff	0.15.10	0.15.18
pytest	9.0.3	9.1.1
pre-commit	4.5.1	4.6.0
ipykernel	7.2.0	7.3.0

Updates transformers from 5.3.0 to 5.12.1

Release notes

Sourced from transformers's releases.

Patch release v5.12.1

Updated the lower bound for PEFT and a fix for auto tokenizer to properly resolve the mistral tokenizer (when mistral-common is installed). This is similar to v.5.10.3 minus the fixes that were already included in the main release - vLLM will first target 5.10.3 🤗

• Fix peft lower bound #46605 by @​hmellor (#46605)
• mistral common backend fix #46667 by @​itazap (#46667)

Full Changelog: huggingface/transformers@v5.12.0...v5.12.1

Patch release v5.10.4

Update: Note that on pypi 5.10.3 doesn't exist and this this saved under 5.10.4 (so essentially a minor version skipped). Sorry about that, that's on me. Just wanted to clarify to make this less confusing!

A few fixes needed for vLLM to sync with transformers 🤗

• [fix] regression introduced by #45534 #46456 by @​eustlb (#46456)
• Fix {image/video/audio}_token_ids in ProcessorMixin #46500 by @​hmellor (#46500)
• Fix InternVL models #46524 by @​hmellor (#46524)
• Fix the offsets in processing #46525 by @​zucchini-nlp (#46525)
• Fix peft lower bound #46605 by @​hmellor (#46605)
• mistral common backend fix #46667 by @​itazap (#46667)

Full Changelog: huggingface/transformers@v5.10.2...v5.10.3

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)

... (truncated)

Commits

• ddb849a v5.12.1
• d81db16 mistral common backend fix (#46667)
• 07c294c Fix peft lower bound (#46605)
• 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)
• Additional commits viewable in compare view

Updates huggingface-hub from 1.10.2 to 1.20.1

Release notes

Sourced from huggingface-hub's releases.

[v1.20.0] Browser-based OAuth login, multi-commit folder uploads, and more

🔒 Browser-based OAuth login

hf auth login now defaults to a browser-based OAuth Device Code flow instead of asking you to copy-paste a token. The command prints a URL and a short code, you authorize in the browser, and the CLI retrieves and saves the token for you. The same applies to login() in Python. In an interactive terminal you still get a gh-style arrow-key menu to pick between browser login and pasting a token, and --token works exactly as before.

OAuth tokens expire after 30 days, but they come with a refresh token: get_token() transparently refreshes them when less than a day of validity remains, so long-running setups keep working without re-authenticating. hf auth list now shows the expiry date for OAuth tokens.

> hf auth login
? How would you like to log in? Log in with your browser
Open this URL in your browser:
    https://hf.co/oauth/device
And enter the code: 52AT-FLYZ
Waiting for authorization.

When the command is run by an AI agent, it never prompts. Instead it streams structured events so the agent can surface the URL and code to its user, then blocks until a terminal auth_success / auth_error event:

$ hf auth login --format json
{"event": "device_code", "verification_uri": "https://hf.co/oauth/device", "user_code": "52AT-FLYZ", "verification_uri_complete": "https://hf.co/oauth/device", "expires_in": 300, "interval": 5}
{"event": "auth_success", "user": "celinah", "token_name": "oauth-celinah"}

hf auth list surfaces the new expiry column:

$ hf auth list
  name          token       expires
- ------------- ----------- -------------------
  my-token      hf_****5678
* oauth-user    hf_****1234 2026-07-09
  oauth-old     hf_****9999 2026-06-09 (expired)

Finally, notebook_login() now renders the link and code with plain IPython.display.HTML, dropping the ipywidgets dependency.

• [Auth] Browser-based OAuth login by @​hanouticelina in #4354

⚡ Faster, more reliable hf upload for large folders

hf upload and the underlying upload_folder have been revamped to be faster and far more robust on large folders. When hf_xet is installed (the default), uploads now run through a streamed, multi-commit pipeline built on the XetSession API: the folder is scanned and fed into a background Xet upload while previous batches are committed in parallel, and files are hashed in a single read pass while they are chunked (the old flow read every large file twice). Nothing changes in how you call it:

hf upload <repo-id> <path/to/folder>

... (truncated)

Commits

• 5efdca0 Release: v1.20.1
• 0c3a062 [Auth] Fix circular import on from huggingface_hub import login (#4384) (#4...
• 8d52526 Release: v1.20.0
• 9379ae3 Release: v1.20.0.rc0
• 3b3abe3 [Spaces] Add wait_for_space API and hf spaces wait CLI (#4380)
• e52fdef [CLI] Make hf jobs ssh wait for job to be running (#4379)
• a0c1dfe [Jobs] Add hf jobs wait and HfApi.wait_for_job (#4345)
• 5589874 [Inference Endpoints] Custom-container deploy CLI + deprecate protected endpo...
• 462d093 [CLI] Suggest creating repo/bucket on NotFound errors (#4372)
• ebe5315 Add new JobNotFound error (#4367)
• 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 2.5.0

Release notes
Sourced from numpy's releases.

v2.5.0 (June 21, 2026)
NumPy 2.5.0 Release Notes
Numpy 2.5.0 is a transitional release. It drops support for Python 3.11,
marking the end of distutils, and expires a large number of deprecations made
in the 2.0.x release. It also improves free threading and brings sorting into
compliance with the array-api standard with the addition of descending sorts.
There is also a fair amount of preparation for Python 3.15, which will be
supported starting with the first rc.
This release supports Python versions 3.12-3.14.
Highlights

Distutils has been removed,
Many expired deprecations, see below,
Many new deprecations, see below,
Many static typing improvements.
Improved support for free threading,
Support for descending sorts,

See New Features below for other additions.
Deprecations


numpy.char.chararray is deprecated. Use an ndarray with a string or bytes dtype instead.
(gh-30605)


numpy.take now correctly checks if the result can be cast to the provided
out=out under the same-kind rule. A DeprecationWarning is given now
when this check fails. Previously, take incorrectly checked if out
could be cast to the result (the wrong direction). This deprecation also
affects compress and possibly other functions. (Future versions of NumPy
may tighten the casting check further.)
(gh-30615)


The numpy.char.[as]array functions are deprecated. Use an
numpy.[as]array with a string or bytes dtype instead.
(gh-30802)


Setting the dtype attribute is deprecated because mutating an array is unsafe
if an array is shared, especially by multiple threads. As an alternative,
you can create a view with a new dtype via array.view(dtype=new_dtype).
(gh-29244)




... (truncated)


Commits

6910b28 Merge pull request #31706 from charris/prepare-2.5.0-release
e0acd2b REL: Prepare for the NumPy 2.5.0 release.
8d928b7 Merge pull request #31704 from charris/backport-31649
c2055ba MAINT: update openblas to 0.3.33.112.0 (#31649)
ce17c81 Merge pull request #31703 from charris/backport-31609
3de6203 BUG: fix StringDType distinct-allocator bugs and add tests (#31609)
c723971 Merge pull request #31700 from charris/backport-31694
64513b2 MAINT: Bump pypa/cibuildwheel from 3.4.1 to 4.1.0
04707f0 Merge pull request #31698 from charris/try-fix-emscripten
5cf0686 MAINT: Try to fix emscripten wheel build.
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 4.68.3

Release notes
Sourced from tqdm's releases.

tqdm v4.68.3 stable

utils: delay os.get_terminal_size (#1763 <- #1760)
autonotebook: support QtConsole, Spyder, JupyterLite (#1763, #1628, #1559 <- #1283, #1098, #512)
minor docs updates

fix typo (#1762)
use git-fame


misc minor framework updates

fix & update CI build
pre-commit: add docs & metadata generation
move tox.ini -> pyproject.toml, move tox-gh-actions -> tox-gh
add Python 3.14, drop 3.7 support



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

9aff609 bump version, merge pull request #1763 from tqdm/jupyterlite
9872f80 drop date from snap version str to fix pydantic
b829334 support QtConsole, Spyder, JupyterLite
6fa4867 delay os.get_terminal_size
748e107 lint
e6e29eb move tox.ini -> pyproject.toml
617e4fa tox-gh-actions -> tox-gh
c49c50d add python 3.14, drop python 3.7 support
fa2bcdb pre-commit: tqdm.1
1ec7988 auto git-fame
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



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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 scipy from 1.17.1 to 1.18.0

Release notes
Sourced from scipy's releases.

SciPy 1.18.0 Release Notes
SciPy 1.18.0 is the culmination of 6 months of hard work. It contains
many new features, numerous bug-fixes, improved test coverage and better
documentation. There have been a number of deprecations and API changes
in this release, which are documented below. All users are encouraged to
upgrade to this release, as there are a large number of bug-fixes and
optimizations. Before upgrading, we recommend that users check that
their own code does not use deprecated SciPy functionality (to do so,
run your code with python -Wd and check for DeprecationWarning s).
Our development attention will now shift to bug-fix releases on the
1.18.x branch, and on adding new features on the main branch.
This release requires Python 3.12-3.14 and NumPy 2.0.0 or greater.
Highlights of this release

SciPy now supports three different build modes for BLAS and LAPACK
LP64/ILP64 support, and machinery is provided for downstream cython_lapack
consumers to gracefully handle LP64/ILP64 backend builds. ILP64 support
has been substantially improved across the SciPy library.
Remaining Fortran to C translations have been completed---an experimental
Fortran-free build option is now available to developers for testing
purposes. Developer feedback is welcome on Fortran-free builds.
scipy.signal.whittaker_henderson now provides access to Whittaker-Henderson
smoothing of a discrete signal.
A large number of scipy.stats functions now support lazy arrays and JAX
JIT. Array API support has been improved substantially in SciPy, with at least
21 functions gaining new support in this release. 16 scipy.stats functions
have also gained support for MArray input.

New features
scipy.fft improvements

SciPy's internal FFT backend has switched from pocketfft to its
successor package ducc0.fft, which features several incremental
improvements. The most significant of those from SciPy's perspective is
probably that storage requirements for internally cached plans have been
significantly reduced for most long 1D transforms. Plans that require more
storage than 1MB will no longer be cached; this mainly affects huge 1D
transforms of prime and near-prime sizes.

scipy.interpolate improvements


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Commits

54ef542 REL: 1.18.0 release commit
a45e463 Merge pull request #25395 from tylerjereddy/treddy_prep_1.18.0_final
ee2442e TYP, MAINT, TST: PR 25395 revisions
3225154 DOC: PR 25395 revisions
14c7bd7 TYP: Fix mypy errors with pytest==9.1.0 (#25410)
71522e9 DOC: revise SciPy 1.18.0 release notes
92f8482 MAINT: fix errors from pytest 9.1 (#25378)
7b27bf4 TST, MAINT: modernize spatial tests for pytest 10 (#25376...
Description has been truncated

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