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Bump transformers from 4.43.4 to 4.47.1 #980

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@dependabot dependabot bot commented on behalf of github Dec 23, 2024

Bumps transformers from 4.43.4 to 4.47.1.

Release notes

Sourced from transformers's releases.

v4.47.1

Patch release v4.47.1

We waited a little bit to make sure it was stable, thanks @​winglian for double checking and everyone for the fixes!

v4.47.0: PaliGemma-2, I-JEPA, OLMo-2, LayerSkip, Tensor Parallel

New models

PaliGemma-2

PaliGemma 2 and PaliGemma are lightweight open vision-language models (VLM) inspired by PaLI-3, and based on open components like the SigLIP vision model and the Gemma language model. PaliGemma takes both images and text as inputs and can answer questions about images with detail and context, meaning that PaliGemma can perform deeper analysis of images and provide useful insights, such as captioning for images and short videos, object detection, and reading text embedded within images.

PaliGemma 2 is available in 3B, 10B, and 28B parameter sizes, which are based on Gemma 2 2B, 9B, and 27B models, respectively. The original PaliGemma models are available in the 3B size. For more information on Gemma model variants, see the Gemma models list. PaliGemma model variants support different pixel resolutions for image inputs, including 224 x 224, 448 x 448, and 896 x 896 pixels.

I-JEPA

The I-JEPA model was proposed in Image-based Joint-Embedding Predictive Architecture by Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael Rabbat, Yann LeCun, Nicolas Ballas. I-JEPA is a self-supervised learning method that predicts the representations of one part of an image based on other parts of the same image. This approach focuses on learning semantic features without relying on pre-defined invariances from hand-crafted data transformations, which can bias specific tasks, or on filling in pixel-level details, which often leads to less meaningful representations.

OLMo 2

The OLMo2 model is the successor of the OLMo model, which was proposed in OLMo: Accelerating the Science of Language Models.

The architectural changes from the original OLMo model to this model are:

  • RMSNorm is used instead of standard layer norm.
  • Norm is applied to attention queries and keys.
  • Norm is applied after attention/feedforward layers rather than before.

... (truncated)

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Bumps [transformers](https://github.com/huggingface/transformers) from 4.43.4 to 4.47.1.
- [Release notes](https://github.com/huggingface/transformers/releases)
- [Commits](huggingface/transformers@v4.43.4...v4.47.1)

---
updated-dependencies:
- dependency-name: transformers
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot added the dependencies Pull requests that update a dependency file label Dec 23, 2024
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Dependency Review

✅ No vulnerabilities or license issues or OpenSSF Scorecard issues found.

OpenSSF Scorecard

PackageVersionScoreDetails
pip/transformers 4.47.1 🟢 4.4
Details
CheckScoreReason
Code-Review🟢 9Found 29/30 approved changesets -- score normalized to 9
Maintained🟢 1030 commit(s) and 20 issue activity found in the last 90 days -- score normalized to 10
Security-Policy🟢 10security policy file detected
CII-Best-Practices⚠️ 0no effort to earn an OpenSSF best practices badge detected
Dangerous-Workflow⚠️ 0dangerous workflow patterns detected
License🟢 10license file detected
Token-Permissions⚠️ 0detected GitHub workflow tokens with excessive permissions
Branch-Protection⚠️ -1internal error: error during branchesHandler.setup: internal error: githubv4.Query: Resource not accessible by integration
Binary-Artifacts🟢 10no binaries found in the repo
Signed-Releases⚠️ -1no releases found
Packaging🟢 10packaging workflow detected
Fuzzing⚠️ 0project is not fuzzed
SAST⚠️ 0SAST tool is not run on all commits -- score normalized to 0
Pinned-Dependencies⚠️ 0dependency not pinned by hash detected -- score normalized to 0
Vulnerabilities⚠️ 0464 existing vulnerabilities detected

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  • setup.py

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