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winstxnhdw / nllb-api

A performant high-throughput CPU-based API for Meta's No Language Left Behind (NLLB) using CTranslate2, hosted on Hugging Face Spaces.
https://huggingface.co/spaces/winstxnhdw/nllb-api
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build(deps): bump the dependencies group with 2 updates #186

Closed dependabot[bot] closed 5 months ago

dependabot[bot] commented 5 months ago

Bumps the dependencies group with 2 updates: transformers and ruff.

Updates transformers from 4.41.2 to 4.42.2

Release notes

Sourced from transformers's releases.

Patch release v4.42.2

Patch release

Thanks to our 2 contributors for their prompt fixing mostly applies for training and FA2!

v4.42.1: Patch release

Patch release for commit:

  • [HybridCache] Fix get_seq_length method (#31661)

v4.42.0: Gemma 2, RTDETR, InstructBLIP, LLAVa Next, New Model Adder

New model additions

Gemma-2

The Gemma2 model was proposed in Gemma2: Open Models Based on Gemini Technology and Research by Gemma2 Team, Google. Gemma2 models are trained on 6T tokens, and released with 2 versions, 2b and 7b.

The abstract from the paper is the following:

This work introduces Gemma2, a new family of open language models demonstrating strong performance across academic benchmarks for language understanding, reasoning, and safety. We release two sizes of models (2 billion and 7 billion parameters), and provide both pretrained and fine-tuned checkpoints. Gemma2 outperforms similarly sized open models on 11 out of 18 text-based tasks, and we present comprehensive evaluations of safety and responsibility aspects of the models, alongside a detailed description of our model development. We believe the responsible release of LLMs is critical for improving the safety of frontier models, and for enabling the next wave of LLM innovations

image

RTDETR

The RT-DETR model was proposed in DETRs Beat YOLOs on Real-time Object Detection by Wenyu Lv, Yian Zhao, Shangliang Xu, Jinman Wei, Guanzhong Wang, Cheng Cui, Yuning Du, Qingqing Dang, Yi Liu.

RT-DETR is an object detection model that stands for “Real-Time DEtection Transformer.” This model is designed to perform object detection tasks with a focus on achieving real-time performance while maintaining high accuracy. Leveraging the transformer architecture, which has gained significant popularity in various fields of deep learning, RT-DETR processes images to identify and locate multiple objects within them.

image

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.

InstructBLIP uses the same architecture as BLIP-2 with a tiny but important difference: it also feeds the text prompt (instruction) to the Q-Former.

image

LlaVa NeXT Video

... (truncated)

Commits


Updates ruff from 0.4.10 to 0.5.0

Release notes

Sourced from ruff's releases.

0.5.0

Release Notes

Check out the blog post for a migration guide and overview of the changes!

Breaking changes

See also, the "Remapped rules" section which may result in disabled rules.

  • Follow the XDG specification to discover user-level configurations on macOS (same as on other Unix platforms)
  • Selecting ALL now excludes deprecated rules
  • [flake8-bandit] Modify diagnostic ranges for shell-related rules (#10667)
  • The released archives now include an extra level of nesting, which can be removed with --strip-components=1 when untarring.
  • The release artifact's file name no longer includes the version tag. This enables users to install via /latest URLs on GitHub.

Deprecations

The following rules are now deprecated:

Remapped rules

The following rules have been remapped to new rule codes:

Stabilization

The following rules have been stabilized and are no longer in preview:

... (truncated)

Changelog

Sourced from ruff's changelog.

0.5.0

Check out the blog post for a migration guide and overview of the changes!

Breaking changes

See also, the "Remapped rules" section which may result in disabled rules.

  • Follow the XDG specification to discover user-level configurations on macOS (same as on other Unix platforms)
  • Selecting ALL now excludes deprecated rules
  • The released archives now include an extra level of nesting, which can be removed with --strip-components=1 when untarring.
  • The release artifact's file name no longer includes the version tag. This enables users to install via /latest URLs on GitHub.

Deprecations

The following rules are now deprecated:

Remapped rules

The following rules have been remapped to new rule codes:

Stabilization

The following rules have been stabilized and are no longer in preview:

... (truncated)

Commits
  • 244b923 Add necessary permissions for cargo-dist Docker build (#12072)
  • a8b48fc Release v0.5.0 (#12068)
  • 04c8597 [flake8-simplify] Stabilize detection of Yoda conditions for "constant" col...
  • 4029a25 [Ruff v0.5] Stabilise 15 pylint rules (#12051)
  • 0917ce1 Update documentation to mention etcetera crate instead of dirs for user c...
  • 22cebdf Add server config to filter out syntax error diagnostics (#12059)
  • 72b6c26 Simplify LinterResult, avoid cloning ParseError (#11903)
  • 73851e7 Avoid displaying syntax error as log message (#11902)
  • e7b4969 Remove E999 as a rule, disallow any disablement methods for syntax error (#...
  • c98d8a0 [pyflakes] Stabilize detection of is comparisons to lists, etc. (F632) (#...
  • Additional commits viewable in compare view


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