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Bumps the pip group with 4 updates in the / directory: nltk, torch, tqdm and transformers.

Updates nltk from 3.7 to 3.9.2

Changelog

Sourced from nltk's changelog.

Version 3.9.2 2025-10-01

  • Update download checksums to use SHA256 in built index
  • Fix percentage escape in new-style string formatting
  • replace shortened URLs using goo.gl
  • Make Wordnet interoperable with various taggers and tagged corpora
  • Fix saving PerceptronTagger
  • Document how to reproduce old Wordnet studies
  • properly initialize Portuguese corpus reader
  • support for mixed rules conversion into Chomsky Normal Form
  • only import tkinter if a GUI is needed
  • issue #2112 with Corenlp
  • new environment variable NLTK_DOWNLOADER_FORCE_INTERACTIVE_SHELL
  • Lesk defaults to most frequent sense in case of ties

Thanks to the following contributors to 3.9.2: Jose Cols, Peter de Blanc, GeneralPoxter, Eric Kafe, William LaCroix, Jason Liu, Samer Masterson, Mike014, purificant, Andrew Ernest Ritz, samertm, Ikram Ul Haq, Christopher Smith, Ryan Mannion

Version 3.9.1 2024-08-19

  • Fixed bug that prevented wordnet from loading

Version 3.9 2024-08-18

  • Fix security vulnerability CVE-2024-39705 (breaking change)
  • Replace pickled models (punkt, chunker, taggers) by new pickle-free "_tab" packages
  • No longer sort Wordnet synsets and relations (sort in calling function when required)
  • Only strip the last suffix in Wordnet Morphy, thus restricting synsets() results
  • Add Python 3.12 support
  • Many other minor fixes

Thanks to the following contributors to 3.8.2: Tom Aarsen, Cat Lee Ball, Veralara Bernhard, Carlos Brandt, Konstantin Chernyshev, Michael Higgins, Eric Kafe, Vivek Kalyan, David Lukes, Rob Malouf, purificant, Alex Rudnick, Liling Tan, Akihiro Yamazaki.

Version 3.8.1 2023-01-02

  • Resolve RCE vulnerability in localhost WordNet Browser (#3100)
  • Remove unused tool scripts (#3099)
  • Resolve XSS vulnerability in localhost WordNet Browser (#3096)
  • Add Python 3.11 support (#3090)

Thanks to the following contributors to 3.8.1: Francis Bond, John Vandenberg, Tom Aarsen

Version 3.8 2022-12-12

  • Refactor dispersion plot (#3082)
  • Provide type hints for LazyCorpusLoader variables (#3081)
  • Throw warning when LanguageModel is initialized with incorrect vocabulary (#3080)

... (truncated)

Commits
  • 4e17ea3 Updates for 3.9.2
  • 77ed66b Merge pull request #3425 from ekaf/ci-blank-data
  • 13d6791 Update .github/workflows/ci.yml
  • d2cf5d4 Ensure nltk_data path is in the environment
  • 4473fde Test CI with no data
  • 1f1614b Merge pull request #3349 from ShadokDuBas/fix/bug_ccg_logic_side_effect_on_le...
  • 7e9779e Merge pull request #3419 from ekaf/hotfix-3416
  • 83bd737 Merge pull request #3423 from purificant/_dependabot
  • e96cce0 Merge pull request #3422 from purificant/_pre_commit
  • bcf6ea6 Merge pull request #3421 from purificant/_py_versions
  • Additional commits viewable in compare view

Updates torch from 1.11.0 to 2.8.0

Release notes

Sourced from torch's releases.

PyTorch 2.8.0 Release Notes

Highlights

... (truncated)

Changelog

Sourced from torch's changelog.

Releasing PyTorch

Release Compatibility Matrix

Following is the Release Compatibility Matrix for PyTorch releases:

... (truncated)

Commits
  • ba56102 Cherrypick: Add the RunLLM widget to the website (#159592)
  • c525a02 [dynamo, docs] cherry pick torch.compile programming model docs into 2.8 (#15...
  • a1cb3cc [Release Only] Remove nvshmem from list of preload libraries (#158925)
  • c76b235 Move out super large one off foreach_copy test (#158880)
  • 20a0e22 Revert "[Dynamo] Allow inlining into AO quantization modules (#152934)" (#158...
  • 9167ac8 [MPS] Switch Cholesky decomp to column wise (#158237)
  • 5534685 [MPS] Reimplement tri[ul] as Metal shaders (#158867)
  • d19e08d Cherry pick PR 158746 (#158801)
  • a6c044a [cherry-pick] Unify torch.tensor and torch.ops.aten.scalar_tensor behavior (#...
  • 620ebd0 [Dynamo] Use proper sources for constructing dataclass defaults (#158689)
  • Additional commits viewable in compare view

Updates tqdm from 4.64.0 to 4.66.3

Release notes

Sourced from tqdm's releases.

tqdm v4.66.3 stable

tqdm v4.66.2 stable

  • pandas: add DataFrame.progress_map (#1549)
  • notebook: fix HTML padding (#1506)
  • keras: fix resuming training when verbose>=2 (#1508)
  • fix format_num negative fractions missing leading zero (#1548)
  • fix Python 3.12 DeprecationWarning on import (#1519)
  • linting: use f-strings (#1549)
  • update tests (#1549)
  • CI: bump actions (#1549)

tqdm v4.66.1 stable

  • fix utils.envwrap types (#1493 <- #1491, #1320 <- #966, #1319)
    • e.g. cloudwatch & kubernetes workaround: export TQDM_POSITION=-1
  • drop mentions of unsupported Python versions

tqdm v4.66.0 stable

  • environment variables to override defaults (TQDM_*) (#1491 <- #1061, #950 <- #614, #1318, #619, #612, #370)
    • e.g. in CI jobs, export TQDM_MININTERVAL=5 to avoid log spam
    • add tests & docs for tqdm.utils.envwrap
  • fix & update CLI completion
  • fix & update API docs
  • minor code tidy: replace os.path => pathlib.Path
  • fix docs image hosting
  • release with CI bot account again (cli/cli#6680)

tqdm v4.65.2 stable

  • exclude examples from distributed wheel (#1492)

tqdm v4.65.1 stable

  • migrate setup.{cfg,py} => pyproject.toml (#1490)
    • fix asv benchmarks
    • update docs
  • fix snap build (#1490)
  • fix & update tests (#1490)
    • fix flaky notebook tests
    • bump pre-commit
    • bump workflow actions

tqdm v4.65.0 stable

  • add Python 3.11 and drop Python 3.6 support (#1439, #1419, #502 <- #720, #620)
  • misc code & docs tidy
  • fix & update CI workflows & tests

tqdm v4.64.1 stable

... (truncated)

Commits

Updates transformers from 4.18.0 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)

Commits

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@dependabot
Bump the pip group across 1 directory with 4 updates
f84aba2 
Bumps the pip group with 4 updates in the / directory: [nltk](https://github.com/nltk/nltk), [torch](https://github.com/pytorch/pytorch), [tqdm](https://github.com/tqdm/tqdm) and [transformers](https://github.com/huggingface/transformers).


Updates `nltk` from 3.7 to 3.9.2
- [Changelog](https://github.com/nltk/nltk/blob/develop/ChangeLog)
- [Commits](nltk/nltk@3.7...3.9.2)

Updates `torch` from 1.11.0 to 2.8.0
- [Release notes](https://github.com/pytorch/pytorch/releases)
- [Changelog](https://github.com/pytorch/pytorch/blob/main/RELEASE.md)
- [Commits](pytorch/pytorch@v1.11.0...v2.8.0)

Updates `tqdm` from 4.64.0 to 4.66.3
- [Release notes](https://github.com/tqdm/tqdm/releases)
- [Commits](tqdm/tqdm@v4.64.0...v4.66.3)

Updates `transformers` from 4.18.0 to 4.53.0
- [Release notes](https://github.com/huggingface/transformers/releases)
- [Commits](huggingface/transformers@v4.18.0...v4.53.0)

---
updated-dependencies:
- dependency-name: nltk
  dependency-version: 3.9.2
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: torch
  dependency-version: 2.8.0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: tqdm
  dependency-version: 4.66.3
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: transformers
  dependency-version: 4.53.0
  dependency-type: direct:production
  dependency-group: pip
...

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@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python Pull requests that update python code labels Feb 20, 2026
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