Bump transformers from 4.43.3 to 4.45.2

[dependabot]

Bumps transformers from 4.43.3 to 4.45.2.

Release notes

Sourced from transformers's releases.

Release v4.45.2

Patch release v4.45.2

Mostly some warnings that were not properly removed ⚠️ :

• Ignore keys on validate_rope #33753 by @​zucchini-nlp
• remove warning v2 #33761 by @​itazap
• Config: lower save_pretrained exception to warning #33906 by @​gante

🔴 Had a small regression with dynamic Cache 🔴 *Cache: revert DynamicCache init for BC #33861 by @​gante

A small fix for idefic 🐩 :

• Fixes for issue #33763 in idefics2 model #33766 by @​aroun-coumar

And a fix for Siglip 🤧 !

• hot fix self.position_embeddings->self.position_embedding #33958 and properly fix and RUN_SLOW #33965 thanks to @​mranzinger

Patch Release v4.45.1

Patches for v4.45.1

• [MllamaProcessor] Update errors and API with multiple image (#33715) by @​ArthurZucker
• Generate: can_generate() recursive check (#33718) by @​gante
• clean_up_tokenization_spaces=False if unset (#31938) by @​itazap

Llama 3.2, mllama, Qwen2-Audio, Qwen2-VL, OLMoE, Llava Onevision, Pixtral, FalconMamba, Modular Transformers

New model additions

mllama

The Llama 3.2-Vision collection of multimodal large language models (LLMs) is a collection of pretrained and instruction-tuned image reasoning generative models in 11B and 90B sizes (text + images in / text out). The Llama 3.2-Vision instruction-tuned models are optimized for visual recognition, image reasoning, captioning, and answering general questions about an image. The models outperform many of the available open source and closed multimodal models on common industry benchmarks.

• Add MLLama #33703, by @​qubvel, @​zucchini-nlp, @​ArthurZucker

Qwen2-VL

The Qwen2-VL is a major update from the previous Qwen-VL by the Qwen team.

An extract from the Qwen2-VL blogpost available here is as follows:

Qwen2-VL is the latest version of the vision language models based on Qwen2 in the Qwen model familities. Compared with Qwen-VL, Qwen2-VL has the capabilities of:

• SoTA understanding of images of various resolution & ratio: Qwen2-VL achieves state-of-the-art performance on visual understanding benchmarks, including MathVista, DocVQA, RealWorldQA, MTVQA, etc.
• Understanding videos of 20min+: Qwen2-VL can understand videos over 20 minutes for high-quality video-based question answering, dialog, content creation, etc.
• Agent that can operate your mobiles, robots, etc.: with the abilities of complex reasoning and decision making, Qwen2-VL can be integrated with devices like mobile phones, robots, etc., for automatic operation based on visual environment and text instructions.
• Multilingual Support: to serve global users, besides English and Chinese, Qwen2-VL now supports the understanding of texts in different languages inside images, including most European languages, Japanese, Korean, Arabic, Vietnamese, etc.

... (truncated)

Commits

• 53fad64 v4.45.2
• 2fd49d2 Cache: revert DynamicCache init for BC (#33861)
• 5df4ca8 wow
• 277ed58 fix post cherry-picking!
• b1c237f Fix Tensor + Embedding error in some cases when using SiglipVisionModel (#33994)
• ae5f491 properly fix and RUN_SLOW (#33965)
• 6ea04aa Cache: revert DynamicCache init for BC (#33861)
• be96843 hot fix self.position_embeddings->self.position_embedding (#33958)
• 333ec0a Ignore keys on validate_rope (#33753)
• 3576fec Config: lower save_pretrained exception to warning (#33906)
• Additional commits viewable in compare view

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[dependabot]

Superseded by #666.