Bump transformers from 4.36.0 to 4.41.0

[dependabot]

Bumps transformers from 4.36.0 to 4.41.0.

Release notes

Sourced from transformers's releases.

v4.41.0: Phi3, JetMoE, PaliGemma, VideoLlava, Falcon2, FalconVLM & GGUF support

New models

Phi3

The Phi-3 model was proposed in Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone by Microsoft.

TLDR; Phi-3 introduces new ROPE scaling methods, which seems to scale fairly well! A 3b and a Phi-3-mini is available in two context-length variants—4K and 128K tokens. It is the first model in its class to support a context window of up to 128K tokens, with little impact on quality.

• Phi-3 by @​gugarosa in huggingface/transformers#30423

JetMoE

JetMoe-8B is an 8B Mixture-of-Experts (MoE) language model developed by Yikang Shen and MyShell. JetMoe project aims to provide a LLaMA2-level performance and efficient language model with a limited budget. To achieve this goal, JetMoe uses a sparsely activated architecture inspired by the ModuleFormer. Each JetMoe block consists of two MoE layers: Mixture of Attention Heads and Mixture of MLP Experts. Given the input tokens, it activates a subset of its experts to process them. This sparse activation schema enables JetMoe to achieve much better training throughput than similar size dense models. The training throughput of JetMoe-8B is around 100B tokens per day on a cluster of 96 H100 GPUs with a straightforward 3-way pipeline parallelism strategy.

• Add JetMoE model by @​yikangshen in huggingface/transformers#30005

PaliGemma

PaliGemma is a lightweight open vision-language model (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.

More than 120 checkpoints are released see the collection here !

• Add PaliGemma by @​molbap in huggingface/transformers#30814

VideoLlava

Video-LLaVA exhibits remarkable interactive capabilities between images and videos, despite the absence of image-video pairs in the dataset.

💡 Simple baseline, learning united visual representation by alignment before projection With the binding of unified visual representations to the language feature space, we enable an LLM to perform visual reasoning capabilities on both images and videos simultaneously. 🔥 High performance, complementary learning with video and image Extensive experiments demonstrate the complementarity of modalities, showcasing significant superiority when compared to models specifically designed for either images or videos.

• Add Video Llava by @​zucchini-nlp in huggingface/transformers#29733

Falcon 2 and FalconVLM:

... (truncated)

Commits

• 4c6c45b Release: v4.41.0
• e9a8041 update release script (#30880)
• 0a9300f Support arbitrary processor (#30875)
• 57edd84 [whisper] fix multilingual fine-tuning (#30865)
• 977ce58 Fix dependencies for image classification example (#30842)
• 3802e78 Enable device map (#30870)
• 57c965a Remove deprecated logic and warnings (#30743)
• 3d7d3a8 TEST: Add llama logits tests (#30835)
• 15c74a2 Fix VideoLlava imports (#30867)
• 4e17e7d TST / Quantization: Reverting to torch==2.2.1 (#30866)
• Additional commits viewable in compare view

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