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Bump transformers from 5.0.0rc1 to 5.10.1 in /tools/mlx-smoke - #98

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Bumps transformers from 5.0.0rc1 to 5.10.1.

Release notes

Sourced from transformers's releases.

Release v5.10.1

v5.10.0 was yanked as we publish on a corrupted branch. Sorry everyone, this happens when we rush a release!!!

New Model additions

Gemma4 unified+ Gemma4 MTP

Gemma 4 12B Unified is an encoder-free multimodal model with pretrained and instruction-tuned variants. Unlike standard Gemma 4, which uses dedicated encoder towers, Gemma 4 12B Unified projects raw inputs directly into the language model's embedding space through lightweight linear pipelines. This results in a simpler architecture while maintaining strong multimodal performance.

Key differences from standard Gemma 4:

  • No Vision Tower: Raw pixel patches are projected directly into LM space via a Dense + LayerNorm pipeline with factorized 2D positional embeddings, replacing the vision encoder.
  • No Audio Tower: Raw 16 kHz waveform samples are chunked into fixed-length frames and projected through a simple RMSNorm → Linear pipeline, replacing the mel spectrogram + Conformer encoder.
  • Shared Multimodal Pipeline: Both vision and audio use the same Gemma4UnifiedMultimodalEmbedder (RMSNorm → Linear) for the final projection to text hidden space.

You can find the original Gemma 4 12B Unified checkpoints under the Gemma 4 release.

Sapiens2

Sapiens2 is a family of high-resolution vision transformers pretrained on ~1 billion curated human images, designed for human-centric computer vision tasks including pose estimation, body-part segmentation, surface normal estimation, and pointmap estimation. The models scale from 0.4B to 5B parameters and train at native 1K resolution, with hierarchical 4K variants for extended spatial reasoning. Sapiens2 achieves substantial improvements over its predecessor with +4 mAP in pose estimation, +24.3 mIoU in body-part segmentation, and 45.6% error reduction in normal estimation.

Links: Documentation | Paper

DeepSeek-OCR-2

DeepSeek-OCR-2 is an OCR-specialized vision-language model built on a distinctive architecture that combines a SAM ViT-B vision encoder with a Qwen2 hybrid attention encoder, connected through an MLP projector to a DeepSeek-V2 Mixture-of-Experts (MoE) language model. The model features a hybrid attention mechanism that applies bidirectional attention over image tokens and causal attention over query tokens, enabling efficient and accurate document understanding. It supports both plain OCR tasks and grounding capabilities with coordinate-aware output for document conversion to markdown format.

Links: Documentation

Mellum

Mellum is a code-focused Mixture-of-Experts language model developed by JetBrains. It is derived from the Qwen3-MoE architecture with per-layer-type RoPE and interleaved sliding window attention. The model has 12B total parameters with 2.5B active parameters per token, using 64 routed experts with 8 activated per token across 28 layers.

Links: Documentation

Breaking changes

The Gemma4 vision pooler now casts inputs to float32 before scaling to prevent float16 overflow (inf saturation) with large checkpoints, which may cause minor numerical differences in outputs for users running Gemma-4 vision models in float16.

Audio Language Models (ALMs) now have a dedicated base model class without a language modeling head, aligning them with the design of Vision Language Models (VLMs); users relying on the previous model class structure should update their code to use the new base model class where appropriate.

... (truncated)

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Bumps [transformers](https://github.com/huggingface/transformers) from 5.0.0rc1 to 5.10.1.
- [Release notes](https://github.com/huggingface/transformers/releases)
- [Commits](huggingface/transformers@v5.0.0rc1...v5.10.1)

---
updated-dependencies:
- dependency-name: transformers
  dependency-version: 5.10.1
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python Pull requests that update python code labels Sep 23, 2026
seathatflowsinourveins added a commit that referenced this pull request Sep 23, 2026
mlx-lm 0.30.2 pinned transformers==5.0.0rc1, which Dependabot alerts 3-6 flag
(GHSA-xrqw-3rrv-vx5w, GHSA-fgcw-684q-jj6r, GHSA-29pf-2h5f-8g72,
GHSA-69w3-r845-3855), and the lock resolved mlx 0.29.3 (GHSA-j842-xgm4-wf88,
GHSA-w6vg-jg77-2qg6). requirements.in now pins mlx-lm 0.31.3 with floors
transformers>=5.10.0 and mlx>=0.29.4; the lock (same cutoff) resolves mlx
0.32.2, mlx-lm 0.31.3 and transformers 5.17.0. Newer mlx wheels are macOS 14+,
so the lock and the CI diff-check both compile with MACOSX_DEPLOYMENT_TARGET=14.0.
Supersedes Dependabot #97 and #98, whose raw lock edits fail the diff-check.

Co-authored-by: seathatflowsinourveins <[email protected]>
Co-authored-by: Claude Opus 5.5 (1M context) <[email protected]>
@seathatflowsinourveins

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Superseded by #99: mlx-lm 0.31.3 with floors transformers>=5.10.0 and mlx>=0.29.4, lock recompiled with the CI cutoff, which resolves every alert this PR targets. A direct lock edit fails the macOS recompile-and-diff check by design.

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OK, I won't notify you again about this release, but will get in touch when a new version is available. If you'd rather skip all updates until the next major or minor version, let me know by commenting @dependabot ignore this major version or @dependabot ignore this minor version. You can also ignore all major, minor, or patch releases for a dependency by adding an ignore condition with the desired update_types to your config file.

If you change your mind, just re-open this PR and I'll resolve any conflicts on it.

@dependabot
dependabot Bot deleted the dependabot/pip/tools/mlx-smoke/transformers-5.10.1 branch September 23, 2026 03:46
seathatflowsinourveins added a commit that referenced this pull request Sep 23, 2026
…ison's confirmed defects and file its evidence (#121)

* Fix the closed automation catalog's confirmed defects and file the blind-comparison evidence

Correct the stale harden-runner ubuntu-job count (18 of 22 -> 20 of 24,
measured at HEAD with the exact counting method), fix dependabot.yml's
"github-actions only" header and every doc claim that Dependabot owns only
GitHub Actions references now that a deliberately vulnerable pip fixture
entry exists, and fix the decision record: the stale "only the osv-scanner
job holds security-events: write" claim (zizmor-sarif-upload also holds it),
the "separate upload job scans twice" rationale that conflicts with the
chosen design, and add the missing Evidence/Alternatives/Decision/Overturn
elements to the zizmor-online, Scorecard SARIF and dependency-review
sections. Add mutation-checked assertions covering the OSV/zizmor SARIF
upload failure-path semantics to tests/test_workflow_hardening.py.

Record the "Blind comparison (2026-09-23)" section in the decision record
and copy its comparison artifacts into
evidence/artifacts/blind-comparison-20260923/ (with the judgments file's
scratch/home paths redacted and a README listing every file's sha256),
registered in manifests/evidence.json.

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>

* Resolve reviewer findings on the GitHub-automation closure polish

Fix the review's confirmed high/medium findings:
- security-scan.yml section 3 never had only one job holding
  security-events: write (zizmor-online held it from the founding commit
  a9e5180); say so, with the verification command that shows the count.
- Restate the OSV separate-upload-job rejection honestly: it would not
  scan twice, and the real trade-off is the write scope sitting on the
  job that runs a curl-installed binary; mark it keep-but-compare.
- Reword the dependabot.yml header and the two docs/github-automation.md
  passages: ignore: urllib3 suppresses security-update PRs for the
  fixture pin; open-pull-requests-limit: 0 only stops version updates;
  alerts still appear via the dependency graph regardless.
- Restore the sealed 2026-09-22 lane:claude Dependabot why_not_default
  text verbatim in catalogs/landscape/foundation.json, and move the
  pip-fixture correction into a labelled coordinator annotation in the
  layer's limitations list instead of overwriting lane output;
  regenerate layer-verdicts-20260922.json and the handbook with
  build_verdicts.py --write.
- Section 5: cite the observed hosted upload (the first push run on
  4970ba0, dispatch run 35824151483) and scorecard-action's documented
  example workflow at its pinned SHA, not just the source diff.
- Section 4: name zizmor's actual online-only audit classes instead of
  claiming offline analysis covers no secrets class (its secrets audits
  are static). Section 6: replace the #97/#98 "nothing to flag"
  inference with what those PRs actually show (gate latency, not
  threshold behavior).

Fix the low findings:
- tests/test_workflow_hardening.py: the failure-path test read a fixed
  line offset after each step/job marker, so a reordered key or a
  folded if: block scalar could pass vacuously. Add step_block()/
  block_if() helpers that search the whole block and resolve folded
  scalars, and assert zizmor-online's analyzer step carries no
  continue-on-error (a crash there could otherwise still upload a
  partial SARIF). Mutation-verified: reordered uses:/if: with the
  cancelled() guard dropped, added continue-on-error to the analyzer
  step, and folded the upload job's if: with a hidden always() --
  each mutation failed the test before being reverted.

Re-registered all seven changed files in manifests/evidence.json with
scripts/host_receipts.register_file.

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>

* Split the OSV SARIF upload into a tool-free job; resolve the polish review findings

The osv-scanner job held security-events: write while running the installed
scanner on every event; it is now contents: read and a needs/!cancelled()
osv-sarif-upload job (no shell step or installed tool) uploads, matching the
zizmor split. Record sections 3 and 5 are rewritten to match (Scorecard upload
now cited from the code-scanning analyses list). The lane-sourced catalog text is
restored verbatim and its staleness recorded instead; the redacted judgments copy
now replaces only path tokens; the folded-if bypass in the artifact-step test is
closed. Mutation-checked: a folded always(), a lost !cancelled() and a write scope
back on the scan job each fail the suite.

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>

* Resolve the final polish review: re-run-safe artifact names, bypass-proof step checks, corrected citations

Artifact names now include run_attempt so a re-run cannot hit a same-name
conflict. step_block() spans the whole list item and block_if() collects
plain-scalar continuations, so a leading '- if:' or an always() on a continuation
line is caught (mutation-checked). Docs: harden-runner 21 of 25 ubuntu jobs after
the split; Scorecard layout cited to the example the README links
(ossf/scorecard scorecard-analysis.yml @ d13ba3f) and the upload to paginated
analysis ids; the unmerged-branch commit dropped from the grep list; the
redaction and upload-job wording corrected.

Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>

---------

Co-authored-by: seathatflowsinourveins <[email protected]>
Co-authored-by: Claude Opus 5.5 (1M context) <[email protected]>
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