fix(deps): update auto merged updates

[platform-engineering-bot]

This PR contains the following updates:

Package	Type	Update	Change
@langchain/community (source)	dependencies	patch	0.3.23 -> 0.3.26
chromadb	dependencies	patch	1.10.0 -> 1.10.4
orjson (changelog)		patch	==3.10.13 -> ==3.10.15
registry.access.redhat.com/ubi8/nodejs-18-minimal	final	patch	1-86 -> 1-140
registry.access.redhat.com/ubi8/nodejs-18-minimal	stage	patch	1-86 -> 1-140
timm		patch	==1.0.12 -> ==1.0.14

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Release Notes

langchain-ai/langchainjs (@​langchain/community)

v0.3.26

Compare Source

v0.3.25

Compare Source

v0.3.24

Compare Source

ijl/orjson (orjson)

v3.10.15

Compare Source

Changed

• Publish PyPI manylinux aarch64 wheels built and tested on aarch64.
• Publish PyPI musllinux aarch64 and arm7l wheels built and tested on aarch64.
• Publish PyPI manylinux Python 3.13 wheels for i686, arm7l, ppc64le, and s390x.

v3.10.14

Compare Source

Changed

• Specify build system dependency on maturin>=1,<2 again.
• Allocate memory using PyMem_Malloc() and similar APIs for integration
  with pymalloc, mimalloc, and tracemalloc.
• Source distribution does not ship compressed test documents and relevant
  tests skip if fixtures are not present.
• Build now depends on Rust 1.82 or later instead of 1.72.

huggingface/pytorch-image-models (timm)

v1.0.14

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Jan 19, 2025

• Fix loading of LeViT safetensor weights, remove conversion code which should have been deactivated
• Add 'SO150M' ViT weights trained with SBB recipes, decent results, but not optimal shape for ImageNet-12k/1k pretrain/ft
  • vit_so150m_patch16_reg4_gap_256.sbb_e250_in12k_ft_in1k - 86.7% top-1
  • vit_so150m_patch16_reg4_gap_384.sbb_e250_in12k_ft_in1k - 87.4% top-1
  • vit_so150m_patch16_reg4_gap_256.sbb_e250_in12k
• Misc typing, typo, etc. cleanup
• 1.0.14 release to get above LeViT fix out

What's Changed

• Fix nn.Module type hints by @​adamjstewart in https://github.com/huggingface/pytorch-image-models/pull/2400
• Add missing paper title by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2405
• fix 'timm recipe scripts' link by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2404
• fix typo in EfficientNet docs by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2403
• disable abbreviating csv inference output with ellipses by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2402
• fix incorrect LaTeX formulas by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2406
• VGG ConvMlp: fix layer defaults/types by @​adamjstewart in https://github.com/huggingface/pytorch-image-models/pull/2409
• Implement --no-console-results in inference.py by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2408
• LeViT safetensors load is broken by conversion code that wasn't deactivated by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2412
• A few more weights by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2413
• Fix typos by @​JosuaRieder in https://github.com/huggingface/pytorch-image-models/pull/2415

New Contributors

• @​adamjstewart made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2400

Full Changelog: huggingface/pytorch-image-models@v1.0.13...v1.0.14

v1.0.13

Compare Source

Jan 9, 2025

• Add support to train and validate in pure bfloat16 or float16
• wandb project name arg added by https://github.com/caojiaolong, use arg.experiment for name
• Fix old issue w/ checkpoint saving not working on filesystem w/o hard-link support (e.g. FUSE fs mounts)
• 1.0.13 release

Jan 6, 2025

• Add torch.utils.checkpoint.checkpoint() wrapper in timm.models that defaults use_reentrant=False, unless TIMM_REENTRANT_CKPT=1 is set in env.

Dec 31, 2024

• convnext_nano 384x384 ImageNet-12k pretrain & fine-tune. https://huggingface.co/models?search=convnext_nano%20r384
• Add AIM-v2 encoders from https://github.com/apple/ml-aim, see on Hub: https://huggingface.co/models?search=timm%20aimv2
• Add PaliGemma2 encoders from https://github.com/google-research/big_vision to existing PaliGemma, see on Hub: https://huggingface.co/models?search=timm%20pali2
• Add missing L/14 DFN2B 39B CLIP ViT, vit_large_patch14_clip_224.dfn2b_s39b
• Fix existing RmsNorm layer & fn to match standard formulation, use PT 2.5 impl when possible. Move old impl to SimpleNorm layer, it's LN w/o centering or bias. There were only two timm models using it, and they have been updated.
• Allow override of cache_dir arg for model creation
• Pass through trust_remote_code for HF datasets wrapper
• inception_next_atto model added by creator
• Adan optimizer caution, and Lamb decoupled weighgt decay options
• Some feature_info metadata fixed by https://github.com/brianhou0208
• All OpenCLIP and JAX (CLIP, SigLIP, Pali, etc) model weights that used load time remapping were given their own HF Hub instances so that they work with hf-hub: based loading, and thus will work with new Transformers TimmWrapperModel

What's Changed

• Punch cache_dir through model factory / builder / pretrain helpers by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2356
• Yuweihao inception next atto merge by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2360
• Dataset trust remote tweaks by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2361
• Add --dataset-trust-remote-code to the train.py and validate.py scripts by @​grodino in https://github.com/huggingface/pytorch-image-models/pull/2328
• Fix feature_info.reduction by @​brianhou0208 in https://github.com/huggingface/pytorch-image-models/pull/2369
• Add caution to Adan. Add decouple decay option to LAMB. by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2357
• Switching to timm specific weight instances for open_clip image encoders by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2376
• Fix broken image link in Quickstart doc by @​ariG23498 in https://github.com/huggingface/pytorch-image-models/pull/2381
• Supporting aimv2 encoders by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2379
• fix: minor typos in markdowns by @​ruidazeng in https://github.com/huggingface/pytorch-image-models/pull/2382
• Add 384x384 in12k pretrain and finetune for convnext_nano by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2384
• Fixed unfused attn2d scale by @​laclouis5 in https://github.com/huggingface/pytorch-image-models/pull/2387
• Fix MQA V2 by @​laclouis5 in https://github.com/huggingface/pytorch-image-models/pull/2388
• Wrap torch checkpoint() fn to default use_reentrant flag to False and allow env var override by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2394
• Add half-precision (bfloat16, float16) support to train & validate scripts by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2397
• Merging wandb project name chages w/ addition by @​rwightman in https://github.com/huggingface/pytorch-image-models/pull/2398

New Contributors

• @​brianhou0208 made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2369
• @​ariG23498 made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2381
• @​ruidazeng made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2382
• @​laclouis5 made their first contribution in https://github.com/huggingface/pytorch-image-models/pull/2387

Full Changelog: huggingface/pytorch-image-models@v1.0.12...v1.0.13

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