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RHAIENG-540: build(deps): bump transformers from 4.52.4 to 4.53.0 in /jupyter/trustyai/ubi9-python-3.12 #1755

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@dependabot dependabot bot commented on behalf of github Aug 7, 2025

https://issues.redhat.com/browse/RHAIENG-540

Bumps transformers from 4.52.4 to 4.53.0.

Release notes

Sourced from transformers's releases.

Release v4.53.0

Gemma3n

Gemma 3n models are designed for efficient execution on low-resource devices. They are capable of multimodal input, handling text, image, video, and audio input, and generating text outputs, with open weights for pre-trained and instruction-tuned variants. These models were trained with data in over 140 spoken languages.

Gemma 3n models use selective parameter activation technology to reduce resource requirements. This technique allows the models to operate at an effective size of 2B and 4B parameters, which is lower than the total number of parameters they contain. For more information on Gemma 3n's efficient parameter management technology, see the Gemma 3n page.

image

from transformers import pipeline
import torch
pipe = pipeline(
"image-text-to-text",
torch_dtype=torch.bfloat16,
model="google/gemma-3n-e4b",
device="cuda",
)
output = pipe(
"https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/bee.jpg",
text="<image_soft_token> in this image, there is"
)
print(output)

Dia

image

Dia is an opensource text-to-speech (TTS) model (1.6B parameters) developed by Nari Labs. It can generate highly realistic dialogue from transcript including nonverbal communications such as laughter and coughing. Furthermore, emotion and tone control is also possible via audio conditioning (voice cloning).

Model Architecture: Dia is an encoder-decoder transformer based on the original transformer architecture. However, some more modern features such as rotational positional embeddings (RoPE) are also included. For its text portion (encoder), a byte tokenizer is utilized while for the audio portion (decoder), a pretrained codec model DAC is used - DAC encodes speech into discrete codebook tokens and decodes them back into audio.

Kyutai Speech-to-Text

Kyutai STT is a speech-to-text model architecture based on the Mimi codec, which encodes audio into discrete tokens in a streaming fashion, and a Moshi-like autoregressive decoder. Kyutai’s lab has released two model checkpoints:

... (truncated)

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@dependabot dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update python code labels Aug 7, 2025
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@openshift-ci openshift-ci bot requested review from daniellutz and jiridanek August 7, 2025 23:26
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Bumps [transformers](https://github.com/huggingface/transformers) from 4.52.4 to 4.53.0.
- [Release notes](https://github.com/huggingface/transformers/releases)
- [Commits](huggingface/transformers@v4.52.4...v4.53.0)

---
updated-dependencies:
- dependency-name: transformers
  dependency-version: 4.53.0
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <[email protected]>
@dependabot dependabot bot force-pushed the dependabot/pip/jupyter/trustyai/ubi9-python-3.12/transformers-4.53.0 branch from 448f7c4 to feda5ed Compare August 8, 2025 07:16
@openshift-ci openshift-ci bot added size/xxl and removed size/xxl labels Aug 8, 2025
@jiridanek jiridanek changed the title build(deps): bump transformers from 4.52.4 to 4.53.0 in /jupyter/trustyai/ubi9-python-3.12 RHAIENG-540: build(deps): bump transformers from 4.52.4 to 4.53.0 in /jupyter/trustyai/ubi9-python-3.12 Aug 8, 2025
@openshift-ci openshift-ci bot added size/xxl and removed size/xxl labels Aug 8, 2025
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