build(deps): update transformers requirement from <4.46.0,>4.4.0 to >4.4.0,<4.47.0 in /requirements

[dependabot]

Updates the requirements on transformers to permit the latest version.

Release notes

Sourced from transformers's releases.

Release v4.46.0

New model additions

Moshi

The Moshi model was proposed in Moshi: a speech-text foundation model for real-time dialogue by Alexandre Défossez, Laurent Mazaré, Manu Orsini, Amélie Royer, Patrick Pérez, Hervé Jégou, Edouard Grave and Neil Zeghidour.

Moshi is a speech-text foundation model that casts spoken dialogue as speech-to-speech generation. Starting from a text language model backbone, Moshi generates speech as tokens from the residual quantizer of a neural audio codec, while modeling separately its own speech and that of the user into parallel streams. This allows for the removal of explicit speaker turns, and the modeling of arbitrary conversational dynamics. Moshi also predicts time-aligned text tokens as a prefix to audio tokens. This “Inner Monologue” method significantly improves the linguistic quality of generated speech and provides streaming speech recognition and text-to-speech. As a result, Moshi is the first real-time full-duplex spoken large language model, with a theoretical latency of 160ms, 200ms in practice.

• Moshi integration by @​ylacombe in #33624

Zamba

Zamba-7B-v1 is a hybrid between state-space models (Specifically Mamba) and transformer, and was trained using next-token prediction. Zamba uses a shared transformer layer after every 6 mamba blocks. It uses the Mistral v0.1 tokenizer. We came to this architecture after a series of ablations at small scales. Zamba-7B-v1 was pre-trained on 1T tokens of text and code data.

• Add Zamba by @​pglorio in #30950

GLM

The GLM Model was proposed in ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools by GLM Team, THUDM & ZhipuAI.

The abstract from the paper starts with the following:

We introduce ChatGLM, an evolving family of large language models that we have been developing over time. This report primarily focuses on the GLM-4 language series, which includes GLM-4, GLM-4-Air, and GLM-4-9B.

• add Glm by @​Cyrilvallez in #33823

Idefics 3

The Idefics3 model was proposed in Building and better understanding vision-language models: insights and future directions by Hugo Laurençon, Andrés Marafioti, Victor Sanh, and Léo Tronchon.

... (truncated)

Commits

• c2820c9 fix list 3.8
• b298161 v4.46.0
• b0f0c61 Add SynthID (watermerking by Google DeepMind) (#34350)
• e50bf61 Fix red CI: benchmark script (#34351)
• c42b322 skip test_pipeline_depth_estimation temporarily (#34316)
• d9f7336 Enable Gradient Accumulation fix across all models + trainer fully in forward...
• 1fb575f Support boolean tool args (#34208)
• 343c8cb Added Deberta model type support (#34308)
• 5ba85de [docs] Fix Korean toctree (#34324)
• 049682a Example doc for token classification of Llama and Dependent/Copied Models (#3...
• Additional commits viewable in compare view

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📚 Documentation preview 📚: https://torchmetrics--2807.org.readthedocs.build/en/2807/

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 99%. Comparing base (4c75369) to head (4fb6b16).
Report is 1 commits behind head on master.

Additional details and impacted files

@@            Coverage Diff            @@
##           master   #2807      +/-   ##
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+ Coverage      69%     99%     +31%     
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  Files         338      14     -324     
  Lines       18334     170   -18164     
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- Hits        12586     169   -12417     
+ Misses       5748       1    -5747