build(deps): bump transformers from 4.21.3 to 4.35.2 in /review-sentiment/sentiment-backend

[dependabot]

Bumps transformers from 4.21.3 to 4.35.2.

Release notes

Sourced from transformers's releases.

Patch release: v4.35.2

A patch release was made for the following commit:

• [tokenizers] update tokenizers version pin #27494

to fix all the issues with versioning regarding tokenizers and huggingface_hub

Patch release: v4.35.1

A patch release was made for the following three commits:

• Fix FA2 import + deprecation cycle (#27330)
• Fix from_pt flag when loading with safetensors (#27394)
• Default to msgpack for safetensors (#27460)

Safetensors serialization by default, DistilWhisper, Fuyu, Kosmos-2, SeamlessM4T, Owl-v2

New models

Distil-Whisper

Distil-Whisper is a distilled version of Whisper that is 6 times faster, 49% smaller, and performs within 1% word error rate (WER) on out-of-distribution data. It was proposed in the paper Robust Knowledge Distillation via Large-Scale Pseudo Labelling.

Distil-Whisper copies the entire encoder from Whisper, meaning it retains Whisper's robustness to different audio conditions. It only copies 2 decoder layers, which significantly reduces the time taken to auto-regressively generate text tokens:

Distil-Whisper is MIT licensed and directly available in the Transformers library with chunked long-form inference, Flash Attention 2 support, and Speculative Decoding. For details on using the model, refer to the following instructions.

Joint work from @​sanchit-gandhi, @​patrickvonplaten and @​srush.

• [Assistant Generation] Improve Encoder Decoder by @​patrickvonplaten in #26701
• [WhisperForCausalLM] Add WhisperForCausalLM for speculative decoding by @​patrickvonplaten in #27195
• [Whisper, Bart, MBart] Add Flash Attention 2 by @​patrickvonplaten in #27203

Fuyu

The Fuyu model was created by ADEPT, and authored by Rohan Bavishi, Erich Elsen, Curtis Hawthorne, Maxwell Nye, Augustus Odena, Arushi Somani, Sağnak Taşırlar.

The authors introduced Fuyu-8B, a decoder-only multimodal model based on the classic transformers architecture, with query and key normalization. A linear encoder is added to create multimodal embeddings from image inputs.

By treating image tokens like text tokens and using a special image-newline character, the model knows when an image line ends. Image positional embeddings are removed. This avoids the need for different training phases for various image resolutions. With 8 billion parameters and licensed under CC-BY-NC, Fuyu-8B is notable for its ability to handle both text and images, its impressive context size of 16K, and its overall performance.

Joint work from @​molbap, @​pcuenca, @​amyeroberts, @​ArthurZucker

• Add fuyu model by @​molbap in #26911
• Fuyu: improve image processing by @​molbap in #27007

SeamlessM4T

... (truncated)

Commits

• 514de24 Release: v4.35.2
• 7983bca [tokenizers] update tokenizers version pin (#27494)
• 10f3e7b Release: v4.35.1
• 0b2e2de fix copies
• f047370 Fix FA2 import + deprecation cycle (#27330)
• d8fffbe Fix from_pt flag when loading with safetensors (#27394)
• 757171d Default to msgpack for safetensors (#27460)
• f1185a4 Release: v4.35.0
• b6c0c2b Fuyu protection
• fba863b Conda build
• Additional commits viewable in compare view

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