chore: bump transformers from 5.19.0 to 5.20.0

[dependabot]

Bumps transformers from 5.19.0 to 5.20.0.

Release notes

Sourced from transformers's releases.

Release v5.20.0

New Model additions

Muse Spark Open

Muse Spark Open is a multimodal mixture-of-experts model from Meta that takes text, images, audio, and video as input and generates text. It has 816B total parameters (42B active per token) and a context window of up to 1,048,576 tokens shared across modalities. It is trained for agentic coding tasks such as multi-file editing, debugging, and tool use. Checkpoints are available in BF16 and NVFP4 formats.

Links: Documentation | Blog Post

• Add Muse Spark Open (#49644) by @​guarin in #49644

Ling 3.0

Ling 3.0 Flash is a hybrid Mixture-of-Experts language model from InclusionAI. Its decoder groups five Kimi Delta Attention (KDA) layers with one Multi-head Latent Attention (MLA) layer. The MLA blocks use interleaved rotary embeddings and a head-wise output gate, and the feed-forward blocks combine routed and shared experts. It is natively supported in Transformers as BailingHybridForCausalLM, so it loads without trust_remote_code=True.

Links: Documentation

• [Model] Add native Ling 3.0 Flash support (#49446) by @​icavan in #49446

Kolibri1

Kolibri 1 is Aleph Alpha's mixture-of-experts reasoning model, focused on German and English. Each of its 50 layers routes every token to 6 of 384 experts using sigmoid routing, and adds one shared expert. Four sliding-window attention layers alternate with one full-attention layer, and RoPE is applied only in the sliding-window layers.

Links: Documentation

• Add Kolibri 1 (#49463) by @​lucamotz in #49463

MiniCPM-V 4.7

MiniCPM-V is a series of efficient multimodal large language models developed by OpenBMB. Like MiniCPM-V 4.6, the MiniCPM-V 4.7 architecture pairs a SigLIP vision encoder that has a window-attention merger with a Qwen3.5 language model backbone, and supports both 4x and 16x visual downsampling modes.

The main addition over 4.6 is canvas M-RoPE: instead of numbering visual tokens along a single 1-D sequence, the model lays every image out on a 2-D canvas and assigns each visual token a (temporal, height, width) position, so slices of the same image keep their spatial relationship and video frames keep their temporal order.

• Fix more stuff (#48979) by @​zucchini-nlp in #48979

UnlimitedOcr

UnlimitedOcr is a single 3B-parameter OCR model from Baidu with a standard 32,768-token context length. It builds on DeepSeek OCR and replaces all decoder attention layers with Reference Sliding Window Attention (R-SWA). This keeps the KV cache constant during decoding, so the model can transcribe dozens of pages in a single forward pass. It supports "gundam" mode (640x640 tiles with dynamic cropping) and "base" mode (a single 1024x1024 view), and it can output region detections with bounding boxes.

Links: Documentation | Paper

• Add Unlimited OCR (#46836) by @​guarin in #46836

UltraBERT

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Commits

• 48e4bcd v5.20.0
• 487dcfa Add Muse Spark Open (#49644)
• d2e102b [docs] Hardware docs template (#49575)
• 9d59c2c Add MOSS-Transcribe-Diarize model (#48386)
• 4c6f255 Integrate the UltraBERT architecture (#49596)
• b0eff17 Add MIC contract lock files for PR CI integration (#49631)
• e62ee80 FSDP x TP Saving / Loading, Optimizer (#49256)
• 5789b6d Add Unlimited OCR (#46836)
• 89d1c88 FSDP x TP Saving / Loading (#48802)
• 2b8b231 Use aiter-rope version 3 on ROCm (#49595)
• Additional commits viewable in compare view

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