chore(deps): bump transformers from 5.7.0 to 5.8.0 in /cmd/runtimes/deepspeed

[dependabot]

Bumps transformers from 5.7.0 to 5.8.0.

Release notes

Sourced from transformers's releases.

Release 5.8.0

Release v5.8.0

New Model additions

DeepSeek-V4

DeepSeek-V4 is the next-generation MoE (Mixture of Experts) language model from DeepSeek that introduces several architectural innovations over DeepSeek-V3. The architecture replaces Multi-head Latent Attention (MLA) with a hybrid local + long-range attention design, swaps residual connections for Manifold-Constrained Hyper-Connections (mHC), and bootstraps the first few MoE layers with a static token-id → expert-id hash table. This implementation covers DeepSeek-V4-Flash, DeepSeek-V4-Pro, and their -Base pretrained variants, which share the same architecture but differ in width, depth, expert count and weights.

Links: Documentation | Paper

• Add DeepSeek V4 (#45643) by @​ArthurZucker in #45643

Gemma 4 Assistant

Gemma 4 Assistant is a small, text-only model that enables speculative decoding for Gemma 4 models using the Multi-Token Prediction (MTP) method and associated candidate generator. The model shares the same Gemma4TextModel backbone as other Gemma 4 models but uses KV sharing throughout the entire model, allowing it to reuse the KV cache populated by the target model and skip the pre-fill phase entirely. This architecture includes cross-attention to make the most of the target model's context, allowing the assistant to accurately predict more drafted tokens per drafting round.

Links: Documentation

• First model (#45788) by @​SindhuRaghuram97 in #45788

GraniteSpeechPlus

Granite Speech Plus is a variant of Granite Speech that enhances the projector by consuming the concatenation of the encoder's final hidden states with an arbitrary subset of its intermediate hidden states along the feature dimension. It is a multimodal speech-to-text model that can transcribe audio, provide speaker annotation and word level timestamps by responding to text prompts. The model inherits the same architecture components as Granite Speech including the speech encoder, query transformer projector, language model, and optional LoRA adapter.

Links: Documentation

• Support for a new Granite-Speech-Plus model (#45695) by @​zvik in #45695

Granite4Vision

Granite Vision 4.1 is a vision-language model from IBM Research designed for enterprise-grade document data extraction. It specializes in chart extraction (Chart2CSV, Chart2Summary, Chart2Code), table extraction (JSON, HTML, OTSL), and semantic key-value pair extraction. The model builds on LLaVA-NeXT with architectural innovations including SigLIP2 Vision Encoder, Window Q-Former Projectors, and DeepStack Feature Injection with 8 vision-to-LLM injection points.

Links: Documentation

• Add Granite 4.1 Vision (granite4_vision) (#45597) by @​artem-spector in #45597

EXAONE-4.5

EXAONE 4.5 is the first open-weight vision language model developed by LG AI Research, integrating a dedicated visual encoder into the existing EXAONE 4.0 framework to expand multimodal capabilities. The model features 33 billion parameters in total, including 1.2 billion parameters from the vision encoder, and achieves competitive performance in general benchmarks while outperforming similar-sized models in document understanding and Korean contextual reasoning. It builds on EXAONE 4.0 with key enhancements including an expanded vocabulary of 153,600 tokens, support for up to 256K token context windows, and a Multi-Token Prediction (MTP) mechanism.

Links: Documentation | Paper | Blog Post

• Add EXAONE 4.5 implementations (#45471) by @​nuxlear in #45471

PP-FormulaNet

... (truncated)

Commits

• 049d2bf v5.8.0
• 2871caf Add Granite 4.1 Vision (granite4_vision) (#45597)
• aaec109 fix: correct spelling in continuous_api docstring (#45749)
• 7050d0e Fix link to modular transformers documentation (#45746)
• df2f2b5 Gemma4: fix failed test cases (#45568)
• 2c7d385 First model (#45788)
• a6ccf93 Fix CI: Allow more artifacts to be download in CI (#45785)
• 2c432d7 Add concurrency to PR CI workflow file (pr-ci-caller.yml) (#45786)
• 3db570f Reorder decorators for autodoc and dataclass (#45702)
• 136befe Unwrap text_config in AutoModelFor*.from_config (#45770)
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