YeonwooSung / MLOps

Miscellaneous codes and writings for MLOps
GNU General Public License v3.0
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build(deps): bump the pip group across 13 directories with 2 updates #95

Closed dependabot[bot] closed 7 months ago

dependabot[bot] commented 7 months ago

Bumps the pip group with 1 update in the /LLM/autogen/autogen_fastapi_ex directory: idna. Bumps the pip group with 1 update in the /LLM/llama_index/samples/llama-index-milvus-example directory: idna. Bumps the pip group with 2 updates in the /LLM/llama_index/samples/mixtral_ollama directory: idna and transformers. Bumps the pip group with 1 update in the /LLM/src/observe_with_langfuse directory: idna. Bumps the pip group with 1 update in the /data_management/dvc directory: idna. Bumps the pip group with 2 updates in the /ml-serving/custom-serving/fastapi/local_streaming_llm directory: idna and transformers. Bumps the pip group with 2 updates in the /ml-serving/custom-serving/fastapi/ray/ray_distilbert directory: idna and transformers. Bumps the pip group with 2 updates in the /ml-serving/custom-serving/fastapi/ray/ray_stablediffusion directory: idna and transformers. Bumps the pip group with 2 updates in the /ml-serving/custom-serving/fastapi/ray/ray_yolov5s directory: idna and transformers. Bumps the pip group with 1 update in the /model-vcs/mlflow/simple_mlflow_fastapi_k8s directory: idna. Bumps the pip group with 1 update in the /model-vcs/mlflow/sklearn_mlflow directory: idna. Bumps the pip group with 2 updates in the /ray/ray-air-with-gpt-j-6b directory: idna and transformers. Bumps the pip group with 2 updates in the /ray/zerocopy_loading directory: idna and transformers.

Updates idna from 3.4 to 3.7

Release notes

Sourced from idna's releases.

v3.7

What's Changed

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

Full Changelog: https://github.com/kjd/idna/compare/v3.6...v3.7

Changelog

Sourced from idna's changelog.

3.7 (2024-04-11) ++++++++++++++++

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

3.6 (2023-11-25) ++++++++++++++++

  • Fix regression to include tests in source distribution.

3.5 (2023-11-24) ++++++++++++++++

  • Update to Unicode 15.1.0
  • String codec name is now "idna2008" as overriding the system codec "idna" was not working.
  • Fix typing error for codec encoding
  • "setup.cfg" has been added for this release due to some downstream lack of adherence to PEP 517. Should be removed in a future release so please prepare accordingly.
  • Removed reliance on a symlink for the "idna-data" tool to comport with PEP 517 and the Python Packaging User Guide for sdist archives.
  • Added security reporting protocol for project

Thanks Jon Ribbens, Diogo Teles Sant'Anna, Wu Tingfeng for contributions to this release.

Commits
  • 1d365e1 Release v3.7
  • c1b3154 Merge pull request #172 from kjd/optimize-contextj
  • 0394ec7 Merge branch 'master' into optimize-contextj
  • cd58a23 Merge pull request #152 from elliotwutingfeng/dev
  • 5beb28b More efficient resolution of joiner contexts
  • 1b12148 Update ossf/scorecard-action to v2.3.1
  • d516b87 Update Github actions/checkout to v4
  • c095c75 Merge branch 'master' into dev
  • 60a0a4c Fix typo in GitHub Actions workflow key
  • 5918a0e Merge branch 'master' into dev
  • Additional commits viewable in compare view


Updates idna from 3.4 to 3.7

Release notes

Sourced from idna's releases.

v3.7

What's Changed

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

Full Changelog: https://github.com/kjd/idna/compare/v3.6...v3.7

Changelog

Sourced from idna's changelog.

3.7 (2024-04-11) ++++++++++++++++

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

3.6 (2023-11-25) ++++++++++++++++

  • Fix regression to include tests in source distribution.

3.5 (2023-11-24) ++++++++++++++++

  • Update to Unicode 15.1.0
  • String codec name is now "idna2008" as overriding the system codec "idna" was not working.
  • Fix typing error for codec encoding
  • "setup.cfg" has been added for this release due to some downstream lack of adherence to PEP 517. Should be removed in a future release so please prepare accordingly.
  • Removed reliance on a symlink for the "idna-data" tool to comport with PEP 517 and the Python Packaging User Guide for sdist archives.
  • Added security reporting protocol for project

Thanks Jon Ribbens, Diogo Teles Sant'Anna, Wu Tingfeng for contributions to this release.

Commits
  • 1d365e1 Release v3.7
  • c1b3154 Merge pull request #172 from kjd/optimize-contextj
  • 0394ec7 Merge branch 'master' into optimize-contextj
  • cd58a23 Merge pull request #152 from elliotwutingfeng/dev
  • 5beb28b More efficient resolution of joiner contexts
  • 1b12148 Update ossf/scorecard-action to v2.3.1
  • d516b87 Update Github actions/checkout to v4
  • c095c75 Merge branch 'master' into dev
  • 60a0a4c Fix typo in GitHub Actions workflow key
  • 5918a0e Merge branch 'master' into dev
  • Additional commits viewable in compare view


Updates idna from 3.6 to 3.7

Release notes

Sourced from idna's releases.

v3.7

What's Changed

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

Full Changelog: https://github.com/kjd/idna/compare/v3.6...v3.7

Changelog

Sourced from idna's changelog.

3.7 (2024-04-11) ++++++++++++++++

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

3.6 (2023-11-25) ++++++++++++++++

  • Fix regression to include tests in source distribution.

3.5 (2023-11-24) ++++++++++++++++

  • Update to Unicode 15.1.0
  • String codec name is now "idna2008" as overriding the system codec "idna" was not working.
  • Fix typing error for codec encoding
  • "setup.cfg" has been added for this release due to some downstream lack of adherence to PEP 517. Should be removed in a future release so please prepare accordingly.
  • Removed reliance on a symlink for the "idna-data" tool to comport with PEP 517 and the Python Packaging User Guide for sdist archives.
  • Added security reporting protocol for project

Thanks Jon Ribbens, Diogo Teles Sant'Anna, Wu Tingfeng for contributions to this release.

Commits
  • 1d365e1 Release v3.7
  • c1b3154 Merge pull request #172 from kjd/optimize-contextj
  • 0394ec7 Merge branch 'master' into optimize-contextj
  • cd58a23 Merge pull request #152 from elliotwutingfeng/dev
  • 5beb28b More efficient resolution of joiner contexts
  • 1b12148 Update ossf/scorecard-action to v2.3.1
  • d516b87 Update Github actions/checkout to v4
  • c095c75 Merge branch 'master' into dev
  • 60a0a4c Fix typo in GitHub Actions workflow key
  • 5918a0e Merge branch 'master' into dev
  • Additional commits viewable in compare view


Updates transformers from 4.38.0 to 4.39.3

Release notes

Sourced from transformers's releases.

Release v4.39.3

The AWQ issue persisted, and there was a regression reported with beam search and input embeddings.

Changes

  • Fix BC for AWQ quant #29965
  • generate fix breaking change for patch #29976

Patch release v4.39.2

Series of fixes for backwards compatibility (AutoAWQ and other quantization libraries, imports from trainer_pt_utils) and functionality (LLaMA tokenizer conversion)

  • Safe import of LRScheduler #29919
  • [BC] Fix BC for other libraries #29934
  • [LlamaSlowConverter] Slow to Fast better support #29797

Patch release v4.39.1

Patch release to fix some breaking changes to LLaVA model, fixes/cleanup for Cohere & Gemma and broken doctest

Release v4.39.0

v4.39.0

🚨 VRAM consumption 🚨

The Llama, Cohere and the Gemma model both no longer cache the triangular causal mask unless static cache is used. This was reverted by #29753, which fixes the BC issues w.r.t speed , and memory consumption, while still supporting compile and static cache. Small note, fx is not supported for both models, a patch will be brought very soon!

New model addition

Cohere open-source model

Command-R is a generative model optimized for long context tasks such as retrieval augmented generation (RAG) and using external APIs and tools. It is designed to work in concert with Cohere's industry-leading Embed and Rerank models to provide best-in-class integration for RAG applications and excel at enterprise use cases. As a model built for companies to implement at scale, Command-R boasts:

  • Strong accuracy on RAG and Tool Use
  • Low latency, and high throughput
  • Longer 128k context and lower pricing
  • Strong capabilities across 10 key languages
  • Model weights available on HuggingFace for research and evaluation

LLaVA-NeXT (llava v1.6)

Llava next is the next version of Llava, which includes better support for non padded images, improved reasoning, OCR, and world knowledge. LLaVA-NeXT even exceeds Gemini Pro on several benchmarks.

Compared with LLaVA-1.5, LLaVA-NeXT has several improvements:

  • Increasing the input image resolution to 4x more pixels. This allows it to grasp more visual details. It supports three aspect ratios, up to 672x672, 336x1344, 1344x336 resolution.
  • Better visual reasoning and OCR capability with an improved visual instruction tuning data mixture.
  • Better visual conversation for more scenarios, covering different applications.
  • Better world knowledge and logical reasoning.
  • Along with performance improvements, LLaVA-NeXT maintains the minimalist design and data efficiency of LLaVA-1.5. It re-uses the pretrained connector of LLaVA-1.5, and still uses less than 1M visual instruction tuning samples. The largest 34B variant finishes training in ~1 day with 32 A100s.*

... (truncated)

Commits


Updates idna from 3.4 to 3.7

Release notes

Sourced from idna's releases.

v3.7

What's Changed

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

Full Changelog: https://github.com/kjd/idna/compare/v3.6...v3.7

Changelog

Sourced from idna's changelog.

3.7 (2024-04-11) ++++++++++++++++

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

3.6 (2023-11-25) ++++++++++++++++

  • Fix regression to include tests in source distribution.

3.5 (2023-11-24) ++++++++++++++++

  • Update to Unicode 15.1.0
  • String codec name is now "idna2008" as overriding the system codec "idna" was not working.
  • Fix typing error for codec encoding
  • "setup.cfg" has been added for this release due to some downstream lack of adherence to PEP 517. Should be removed in a future release so please prepare accordingly.
  • Removed reliance on a symlink for the "idna-data" tool to comport with PEP 517 and the Python Packaging User Guide for sdist archives.
  • Added security reporting protocol for project

Thanks Jon Ribbens, Diogo Teles Sant'Anna, Wu Tingfeng for contributions to this release.

Commits
  • 1d365e1 Release v3.7
  • c1b3154 Merge pull request #172 from kjd/optimize-contextj
  • 0394ec7 Merge branch 'master' into optimize-contextj
  • cd58a23 Merge pull request #152 from elliotwutingfeng/dev
  • 5beb28b More efficient resolution of joiner contexts
  • 1b12148 Update ossf/scorecard-action to v2.3.1
  • d516b87 Update Github actions/checkout to v4
  • c095c75 Merge branch 'master' into dev
  • 60a0a4c Fix typo in GitHub Actions workflow key
  • 5918a0e Merge branch 'master' into dev
  • Additional commits viewable in compare view


Updates idna from 3.6 to 3.7

Release notes

Sourced from idna's releases.

v3.7

What's Changed

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

Full Changelog: https://github.com/kjd/idna/compare/v3.6...v3.7

Changelog

Sourced from idna's changelog.

3.7 (2024-04-11) ++++++++++++++++

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

3.6 (2023-11-25) ++++++++++++++++

  • Fix regression to include tests in source distribution.

3.5 (2023-11-24) ++++++++++++++++

  • Update to Unicode 15.1.0
  • String codec name is now "idna2008" as overriding the system codec "idna" was not working.
  • Fix typing error for codec encoding
  • "setup.cfg" has been added for this release due to some downstream lack of adherence to PEP 517. Should be removed in a future release so please prepare accordingly.
  • Removed reliance on a symlink for the "idna-data" tool to comport with PEP 517 and the Python Packaging User Guide for sdist archives.
  • Added security reporting protocol for project

Thanks Jon Ribbens, Diogo Teles Sant'Anna, Wu Tingfeng for contributions to this release.

Commits
  • 1d365e1 Release v3.7
  • c1b3154 Merge pull request #172 from kjd/optimize-contextj
  • 0394ec7 Merge branch 'master' into optimize-contextj
  • cd58a23 Merge pull request #152 from elliotwutingfeng/dev
  • 5beb28b More efficient resolution of joiner contexts
  • 1b12148 Update ossf/scorecard-action to v2.3.1
  • d516b87 Update Github actions/checkout to v4
  • c095c75 Merge branch 'master' into dev
  • 60a0a4c Fix typo in GitHub Actions workflow key
  • 5918a0e Merge branch 'master' into dev
  • Additional commits viewable in compare view


Updates idna from 3.6 to 3.7

Release notes

Sourced from idna's releases.

v3.7

What's Changed

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

Full Changelog: https://github.com/kjd/idna/compare/v3.6...v3.7

Changelog

Sourced from idna's changelog.

3.7 (2024-04-11) ++++++++++++++++

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

3.6 (2023-11-25) ++++++++++++++++

  • Fix regression to include tests in source distribution.

3.5 (2023-11-24) ++++++++++++++++

  • Update to Unicode 15.1.0
  • String codec name is now "idna2008" as overriding the system codec "idna" was not working.
  • Fix typing error for codec encoding
  • "setup.cfg" has been added for this release due to some downstream lack of adherence to PEP 517. Should be removed in a future release so please prepare accordingly.
  • Removed reliance on a symlink for the "idna-data" tool to comport with PEP 517 and the Python Packaging User Guide for sdist archives.
  • Added security reporting protocol for project

Thanks Jon Ribbens, Diogo Teles Sant'Anna, Wu Tingfeng for contributions to this release.

Commits
  • 1d365e1 Release v3.7
  • c1b3154 Merge pull request #172 from kjd/optimize-contextj
  • 0394ec7 Merge branch 'master' into optimize-contextj
  • cd58a23 Merge pull request #152 from elliotwutingfeng/dev
  • 5beb28b More efficient resolution of joiner contexts
  • 1b12148 Update ossf/scorecard-action to v2.3.1
  • d516b87 Update Github actions/checkout to v4
  • c095c75 Merge branch 'master' into dev
  • 60a0a4c Fix typo in GitHub Actions workflow key
  • 5918a0e Merge branch 'master' into dev
  • Additional commits viewable in compare view


Updates transformers from 4.38.0 to 4.39.3

Release notes

Sourced from transformers's releases.

Release v4.39.3

The AWQ issue persisted, and there was a regression reported with beam search and input embeddings.

Changes

  • Fix BC for AWQ quant #29965
  • generate fix breaking change for patch #29976

Patch release v4.39.2

Series of fixes for backwards compatibility (AutoAWQ and other quantization libraries, imports from trainer_pt_utils) and functionality (LLaMA tokenizer conversion)

  • Safe import of LRScheduler #29919
  • [BC] Fix BC for other libraries #29934
  • [LlamaSlowConverter] Slow to Fast better support #29797

Patch release v4.39.1

Patch release to fix some breaking changes to LLaVA model, fixes/cleanup for Cohere & Gemma and broken doctest

Release v4.39.0

v4.39.0

🚨 VRAM consumption 🚨

The Llama, Cohere and the Gemma model both no longer cache the triangular causal mask unless static cache is used. This was reverted by #29753, which fixes the BC issues w.r.t speed , and memory consumption, while still supporting compile and static cache. Small note, fx is not supported for both models, a patch will be brought very soon!

New model addition

Cohere open-source model

Command-R is a generative model optimized for long context tasks such as retrieval augmented generation (RAG) and using external APIs and tools. It is designed to work in concert with Cohere's industry-leading Embed and Rerank models to provide best-in-class integration for RAG applications and excel at enterprise use cases. As a model built for companies to implement at scale, Command-R boasts:

  • Strong accuracy on RAG and Tool Use
  • Low latency, and high throughput
  • Longer 128k context and lower pricing
  • Strong capabilities across 10 key languages
  • Model weights available on HuggingFace for research and evaluation

LLaVA-NeXT (llava v1.6)

Llava next is the next version of Llava, which includes better support for non padded images, improved reasoning, OCR, and world knowledge. LLaVA-NeXT even exceeds Gemini Pro on several benchmarks.

Compared with LLaVA-1.5, LLaVA-NeXT has several improvements:

  • Increasing the input image resolution to 4x more pixels. This allows it to grasp more visual details. It supports three aspect ratios, up to 672x672, 336x1344, 1344x336 resolution.
  • Better visual reasoning and OCR capability with an improved visual instruction tuning data mixture.
  • Better visual conversation for more scenarios, covering different applications.
  • Better world knowledge and logical reasoning.
  • Along with performance improvements, LLaVA-NeXT maintains the minimalist design and data efficiency of LLaVA-1.5. It re-uses the pretrained connector of LLaVA-1.5, and still uses less than 1M visual instruction tuning samples. The largest 34B variant finishes training in ~1 day with 32 A100s.*

... (truncated)

Commits


Updates idna from 3.6 to 3.7

Release notes

Sourced from idna's releases.

v3.7

What's Changed

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

Full Changelog: https://github.com/kjd/idna/compare/v3.6...v3.7

Changelog

Sourced from idna's changelog.

3.7 (2024-04-11) ++++++++++++++++

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

3.6 (2023-11-25) ++++++++++++++++

  • Fix regression to include tests in source distribution.

3.5 (2023-11-24) ++++++++++++++++

  • Update to Unicode 15.1.0
  • String codec name is now "idna2008" as overriding the system codec "idna" was not working.
  • Fix typing error for codec encoding
  • "setup.cfg" has been added for this release due to some downstream lack of adherence to PEP 517. Should be removed in a future release so please prepare accordingly.
  • Removed reliance on a symlink for the "idna-data" tool to comport with PEP 517 and the Python Packaging User Guide for sdist archives.
  • Added security reporting protocol for project

Thanks Jon Ribbens, Diogo Teles Sant'Anna, Wu Tingfeng for contributions to this release.

Commits
  • 1d365e1 Release v3.7
  • c1b3154 Merge pull request #172 from kjd/optimize-contextj
  • 0394ec7 Merge branch 'master' into optimize-contextj
  • cd58a23 Merge pull request #152 from elliotwutingfeng/dev
  • 5beb28b More efficient resolution of joiner contexts
  • 1b12148 Update ossf/scorecard-action to v2.3.1
  • d516b87 Update Github actions/checkout to v4
  • c095c75 Merge branch 'master' into dev
  • 60a0a4c Fix typo in GitHub Actions workflow key
  • 5918a0e Merge branch 'master' into dev
  • Additional commits viewable in compare view


Updates transformers from 4.38.0 to 4.39.3

Release notes

Sourced from transformers's releases.

Release v4.39.3

The AWQ issue persisted, and there was a regression reported with beam search and input embeddings.

Changes

  • Fix BC for AWQ quant #29965
  • generate fix breaking change for patch #29976

Patch release v4.39.2

Series of fixes for backwards compatibility (AutoAWQ and other quantization libraries, imports from trainer_pt_utils) and functionality (LLaMA tokenizer conversion)

  • Safe import of LRScheduler #29919
  • [BC] Fix BC for other libraries #29934
  • [LlamaSlowConverter] Slow to Fast better support #29797

Patch release v4.39.1

Patch release to fix some breaking changes to LLaVA model, fixes/cleanup for Cohere & Gemma and broken doctest

Release v4.39.0

v4.39.0

🚨 VRAM consumption 🚨

The Llama, Cohere and the Gemma model both no longer cache the triangular causal mask unless static cache is used. This was reverted by #29753, which fixes the BC issues w.r.t speed , and memory consumption, while still supporting compile and static cache. Small note, fx is not supported for both models, a patch will be brought very soon!

New model addition

Cohere open-source model

Command-R is a generative model optimized for long context tasks such as retrieval augmented generation (RAG) and using external APIs and tools. It is designed to work in concert with Cohere's industry-leading Embed and Rerank models to provide best-in-class integration for RAG applications and excel at enterprise use cases. As a model built for companies to implement at scale, Command-R boasts:

  • Strong accuracy on RAG and Tool Use
  • Low latency, and high throughput
  • Longer 128k context and lower pricing
  • Strong capabilities across 10 key languages
  • Model weights available on HuggingFace for research and evaluation

LLaVA-NeXT (llava v1.6)

Llava next is the next version of Llava, which includes better support for non padded images, improved reasoning, OCR, and world knowledge. LLaVA-NeXT even exceeds Gemini Pro on several benchmarks.

Compared with LLaVA-1.5, LLaVA-NeXT has several improvements:

  • Increasing the input image resolution to 4x more pixels. This allows it to grasp more visual details. It supports three aspect ratios, up to 672x672, 336x1344, 1344x336 resolution.
  • Better visual reasoning and OCR capability with an improved visual instruction tuning data mixture.
  • Better visual conversation for more scenarios, covering different applications.
  • Better world knowledge and logical reasoning.
  • Along with performance improvements, LLaVA-NeXT maintains the minimalist design and data efficiency of LLaVA-1.5. It re-uses the pretrained connector of LLaVA-1.5, and still uses less than 1M visual instruction tuning samples. The largest 34B variant finishes training in ~1 day with 32 A100s.*

... (truncated)

Commits


Updates idna from 3.6 to 3.7

Release notes

Sourced from idna's releases.

v3.7

What's Changed

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

Full Changelog: https://github.com/kjd/idna/compare/v3.6...v3.7

Changelog

Sourced from idna's changelog.

3.7 (2024-04-11) ++++++++++++++++

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

3.6 (2023-11-25) ++++++++++++++++

  • Fix regression to include tests in source distribution.

3.5 (2023-11-24) ++++++++++++++++

  • Update to Unicode 15.1.0
  • String codec name is now "idna2008" as overriding the system codec "idna" was not working.
  • Fix typing error for codec encoding
  • "setup.cfg" has been added for this release due to some downstream lack of adherence to PEP 517. Should be removed in a future release so please prepare accordingly.
  • Removed reliance on a symlink for the "idna-data" tool to comport with PEP 517 and the Python Packaging User Guide for sdist archives.
  • Added security reporting protocol for project

Thanks Jon Ribbens, Diogo Teles Sant'Anna, Wu Tingfeng for contributions to this release.

Commits
  • 1d365e1 Release v3.7
  • c1b3154 Merge pull request #172 from kjd/optimize-contextj
  • 0394ec7 Merge branch 'master' into optimize-contextj
  • cd58a23 Merge pull request #152 from elliotwutingfeng/dev
  • 5beb28b More efficient resolution of joiner contexts
  • 1b12148 Update ossf/scorecard-action to v2.3.1
  • d516b87 Update Github actions/checkout to v4
  • c095c75 Merge branch 'master' into dev
  • 60a0a4c Fix typo in GitHub Actions workflow key
  • 5918a0e Merge branch 'master' into dev
  • Additional commits viewable in compare view


Updates transformers from 4.38.0 to 4.39.3

Release notes

Sourced from transformers's releases.

Release v4.39.3

The AWQ issue persisted, and there was a regression reported with beam search and input embeddings.

Changes

  • Fix BC for AWQ quant #29965
  • generate fix breaking change for patch #29976

Patch release v4.39.2

Series of fixes for backwards compatibility (AutoAWQ and other quantization libraries, imports from trainer_pt_utils) and functionality (LLaMA tokenizer conversion)

  • Safe import of LRScheduler #29919
  • [BC] Fix BC for other libraries #29934
  • [LlamaSlowConverter] Slow to Fast better support #29797

Patch release v4.39.1

Patch release to fix some breaking changes to LLaVA model, fixes/cleanup for Cohere & Gemma and broken doctest

Release v4.39.0

v4.39.0

🚨 VRAM consumption 🚨

The Llama, Cohere and the Gemma model both no longer cache the triangular causal mask unless static cache is used. This was reverted by #29753, which fixes the BC issues w.r.t speed , and memory consumption, while still supporting compile and static cache. Small note, fx is not supported for both models, a patch will be brought very soon!

New model addition

Cohere open-source model

Command-R is a generative model optimized for long context tasks such as retrieval augmented generation (RAG) and using external APIs and tools. It is designed to work in concert with Cohere's industry-leading Embed and Rerank models to provide best-in-class integration for RAG applications and excel at enterprise use cases. As a model built for companies to implement at scale, Command-R boasts:

  • Strong accuracy on RAG and Tool Use
  • Low latency, and high throughput
  • Longer 128k context and lower pricing
  • Strong capabilities across 10 key languages
  • Model weights available on HuggingFace for research and evaluation

LLaVA-NeXT (llava v1.6)

Llava next is the next version of Llava, which includes better support for non padded images, improved reasoning, OCR, and world knowledge. LLaVA-NeXT even exceeds Gemini Pro on several benchmarks.

Compared with LLaVA-1.5, LLaVA-NeXT has several improvements:

  • Increasing the input image resolution to 4x more pixels. This allows it to grasp more visual details. It supports three aspect ratios, up to 672x672, 336x1344, 1344x336 resolution.
  • Better visual reasoning and OCR capability with an improved visual instruction tuning data mixture.
  • Better visual conversation for more scenarios, covering different applications.
  • Better world knowledge and logical reasoning.
  • Along with performance improvements, LLaVA-NeXT maintains the minimalist design and data efficiency of LLaVA-1.5. It re-uses the pretrained connector of LLaVA-1.5, and still uses less than 1M visual instruction tuning samples. The largest 34B variant finishes training in ~1 day with 32 A100s.*

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Commits


Updates idna from 3.6 to 3.7

Release notes

Sourced from idna's releases.

v3.7

What's Changed

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

Full Changelog: https://github.com/kjd/idna/compare/v3.6...v3.7

Changelog

Sourced from idna's changelog.

3.7 (2024-04-11) ++++++++++++++++

  • Fix issue where specially crafted inputs to encode() could take exceptionally long amount of time to process. [CVE-2024-3651]

Thanks to Guido Vranken for reporting the issue.

3.6 (2023-11-25) ++++++++++++++++

  • Fix regression to include tests in source distribution.

3.5 (2023-11-24) ++++++++++++++++

  • Update to Unicode 15.1.0
  • String codec name is now "idna2008" as overriding the system codec "idna" was not working.
  • Fix typing error for codec encoding
  • "setup.cfg" has been added for this release due to some downstream lack of adherence to PEP 517. Should be removed in a future release so please prepare accordingly.
  • Removed reliance on a symlink for the "idna-data" tool to comport with PEP 517 and the Python Packaging User Guide for sdist archives.
  • Added security reporting protocol for project

Thanks Jon Ribbens, Diogo Teles Sant'Anna, Wu Tingfeng for contributions to this release.

Commits
  • 1d365e1 Release v3.7
  • c1b3154 Merge pull request #172 from kjd/optimize-contextj
  • 0394ec7 Merge branch 'master' into optimize-contextj
  • cd58a23 Merge pull request #152 from elliotwutingfeng/dev
  • 5beb28b More efficient resolution of joiner contexts
  • 1b12148 Update ossf/scorecard-action to v2.3.1
  • d516b87 Update Github actions/checkout to v4
  • c095c75 Merge branch 'master' into dev
  • 60a0a4c Fix typo in GitHub Actions workflow key
  • 5918a0e Merge branch 'master' into dev
  • Additional commits viewable in compare view


Updates transformers from 4.38.0 to 4.39.3

Release notes

Sourced from transformers's releases.

Release v4.39.3

The AWQ issue persisted, and there was a regression reported with beam search and input embeddings.

Changes

  • Fix BC for AWQ quant #29965
  • generate fix breaking change for patch #29976

Patch release v4.39.2

Series of fixes for backwards compatibility (AutoAWQ and other quantizat... _Description has been truncated_