Bump transformers from 3.3.1 to 4.31.0

[dependabot]

Bumps transformers from 3.3.1 to 4.31.0.

Release notes

Sourced from transformers's releases.

v4.31.0: Llama v2, MusicGen, Bark, MMS, EnCodec, InstructBLIP, Umt5, MRa, vIvIt

New models

Llama v2

Llama 2 was proposed in LLaMA: Open Foundation and Fine-Tuned Chat Models by Hugo Touvron et al. It builds upon the Llama architecture adding Grouped Query Attention for efficient inference.

• Add support for Llama 2 by @​ArthurZucker in #24891

Musicgen

The MusicGen model was proposed in the paper Simple and Controllable Music Generation by Jade Copet, Felix Kreuk, Itai Gat, Tal Remez, David Kant, Gabriel Synnaeve, Yossi Adi and Alexandre Défossez.

MusicGen is a single stage auto-regressive Transformer model capable of generating high-quality music samples conditioned on text descriptions or audio prompts. The text descriptions are passed through a frozen text encoder model to obtain a sequence of hidden-state representations. MusicGen is then trained to predict discrete audio tokens, or audio codes, conditioned on these hidden-states. These audio tokens are then decoded using an audio compression model, such as EnCodec, to recover the audio waveform.

Through an efficient token interleaving pattern, MusicGen does not require a self-supervised semantic representation of the text/audio prompts, thus eliminating the need to cascade multiple models to predict a set of codebooks (e.g. hierarchically or upsampling). Instead, it is able to generate all the codebooks in a single forward pass.

• Add Musicgen by @​sanchit-gandhi in #24109

Bark

Bark is a transformer-based text-to-speech model proposed by Suno AI in suno-ai/bark.

• Add bark by @​ylacombe in #24086

MMS

The MMS model was proposed in Scaling Speech Technology to 1,000+ Languages by Vineel Pratap, Andros Tjandra, Bowen Shi, Paden Tomasello, Arun Babu, Sayani Kundu, Ali Elkahky, Zhaoheng Ni, Apoorv Vyas, Maryam Fazel-Zarandi, Alexei Baevski, Yossi Adi, Xiaohui Zhang, Wei-Ning Hsu, Alexis Conneau, Michael Auli

• Add MMS CTC Fine-Tuning by @​patrickvonplaten in #24281

EnCodec

The EnCodec neural codec model was proposed in High Fidelity Neural Audio Compression by Alexandre Défossez, Jade Copet, Gabriel Synnaeve, Yossi Adi.

• Add EnCodec model by @​hollance in #23655

InstructBLIP

The InstructBLIP model was proposed in InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning by Wenliang Dai, Junnan Li, Dongxu Li, Anthony Meng Huat Tiong, Junqi Zhao, Weisheng Wang, Boyang Li, Pascale Fung, Steven Hoi. InstructBLIP leverages the BLIP-2 architecture for visual instruction tuning.

• Add InstructBLIP by @​NielsRogge in #23460

Umt5

The UMT5 model was proposed in UniMax: Fairer and More Effective Language Sampling for Large-Scale Multilingual Pretraining by Hyung Won Chung, Xavier Garcia, Adam Roberts, Yi Tay, Orhan Firat, Sharan Narang, Noah Constant.

• [Umt5] Add google's umt5 to transformers by @​ArthurZucker in #24477

MRA

... (truncated)

Commits

• e42587f [Llama2] Add support for Llama 2 (#24891)
• 4400654 Release v4.31.0
• 49eb357 Fix token pass (#24862)
• f42a35e Add bark (#24086)
• c21c373 Add TAPEX to the list of deprecated models (#24859)
• 054e802 fix broken links in READMEs (#24861)
• c965d30 Fix comments for _merge_heads (#24855)
• e4a52b6 Fix is_vision_available (#24853)
• 4f08887 Add Multimodal heading and Document question answering in task_summary.mdx (#...
• 38dfb86 Bump cryptography from 41.0.0 to 41.0.2 in /examples/research_projects/decisi...
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