chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge - #68

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chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge#68
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Updates the requirements on bitsandbytes to permit the latest version.

Release notes

Sourced from bitsandbytes's releases.

0.50.1: RTX Spark Support

This release adds support for additional hardware platforms and improves performance on RTX Spark / DGX Spark.

Highlights

  • Support added for NVIDIA RTX Spark products running Windows on ARM64 (#2038, #2037, #2032)
  • Improved 4bit GEMM dispatch heuristics for NVIDIA GB10 (#2030)
  • Support for AMD CDNA5 hardware (e.g. MI455X)

What's Changed

New Contributors

Full Changelog: bitsandbytes-foundation/bitsandbytes@0.50.0...0.50.1

Changelog

Sourced from bitsandbytes's changelog.

v0.45.1

Improvements:

  • Compatibility for triton>=3.2.0
  • Moved package configuration to pyproject.toml
  • Build system: initial support for NVIDIA Blackwell B100 GPUs, RTX 50 Blackwell series GPUs and Jetson Thor Blackwell.
    • Note: Binaries built for these platforms are not included in this release. They will be included in future releases upon the availability of the upcoming CUDA Toolkit 12.7 and 12.8.

Bug Fixes:

  • Packaging: wheels will no longer include unit tests. (#1478)

Dependencies:

  • Sets the minimum PyTorch version to 2.0.0.

0.45.0

This is a significant release, bringing support for LLM.int8() to NVIDIA Hopper GPUs such as the H100.

As part of the compatibility enhancements, we've rebuilt much of the LLM.int8() code in order to simplify for future compatibility and maintenance. We no longer use the col32 or architecture-specific tensor layout formats while maintaining backwards compatibility. We additionally bring performance improvements targeted for inference scenarios.

Performance Improvements

This release includes broad performance improvements for a wide variety of inference scenarios. See this X thread for a detailed explanation.

Breaking Changes

🤗PEFT users wishing to merge adapters with 8-bit weights will need to upgrade to peft>=0.14.0.

Packaging Improvements

  • The size of our wheel has been reduced by ~43.5% from 122.4 MB to 69.1 MB! This results in an on-disk size decrease from ~396MB to ~224MB.
  • Binaries built with CUDA Toolkit 12.6.2 are now included in the PyPI distribution.
  • The CUDA 12.5.0 build has been updated to CUDA Toolkit 12.5.1.

Deprecations

  • A number of public API functions have been marked for deprecation and will emit FutureWarning when used. These functions will become unavailable in future releases. This should have minimal impact on most end-users.
  • The k-bit quantization features are deprecated in favor of blockwise quantization. For all optimizers, using block_wise=False is not recommended and support will be removed in a future release.
  • As part of the refactoring process, we've implemented many new 8bit operations. These operations no longer use specialized data layouts.

Full Changelog

0.44.1

Bug fixes:

... (truncated)

Commits
  • 37d2a93 Release 0.50.1
  • 0b3a226 Add sm121 (GB10) tier to the 4-bit GEMM dispatch heuristic
  • 557bfc2 build: Add Windows ARM64 build with CUDA 13.4 for RTX Spark (#2038)
  • 930274c Merge pull request #2032 from mfuntowicz/fix/cuda_121_win
  • 0330f40 Merge branch 'main' into fix/cuda_121_win
  • d799cfd Gate /Zc:preprocessor to cl.exe only
  • 915aa03 Merge pull request #2037 from mfuntowicz/docs/rtx-spark-install-guidelines
  • cf86065 docs: add installation instructions for NVIDIA Spark (ARM64) devices
  • b459659 fix: missing compilation flag on recent msvc version
  • a2b90e6 Fix truncated FP4 constant in Triton dequantize_fp4_tree (#2026)
  • Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.

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@dependabot
chore(deps): update bitsandbytes requirement in /fowoco-knowledge
7987916
Updates the requirements on [bitsandbytes](https://github.com/bitsandbytes-foundation/bitsandbytes) to permit the latest version.
- [Release notes](https://github.com/bitsandbytes-foundation/bitsandbytes/releases)
- [Changelog](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/main/CHANGELOG.md)
- [Commits](bitsandbytes-foundation/bitsandbytes@0.44.0...0.50.1)
---
updated-dependencies:
- dependency-name: bitsandbytes
dependency-version: 0.50.1
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
@dependabotdependabotBot added area:knowledge Context Pack·Workflow·공식 출처 관리 priority:P2 일정에 따라 미룰 수 있는 보완 작업 type:chore 유지보수·저장소 설정 작업 labels Aug 24, 2026
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Skip to content
chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge - #68
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chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge#68
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Updates the requirements on bitsandbytes to permit the latest version.
Release notes
Sourced from bitsandbytes's releases.
0.50.1: RTX Spark Support
This release adds support for additional hardware platforms and improves performance on RTX Spark / DGX Spark.
Highlights
  • Support added for NVIDIA RTX Spark products running Windows on ARM64 (#2038, #2037, #2032)
  • Improved 4bit GEMM dispatch heuristics for NVIDIA GB10 (#2030)
  • Support for AMD CDNA5 hardware (e.g. MI455X)
What's Changed
New Contributors
Full Changelog: bitsandbytes-foundation/bitsandbytes@0.50.0...0.50.1
Changelog
Sourced from bitsandbytes's changelog.
v0.45.1
Improvements:
  • Compatibility for triton>=3.2.0
  • Moved package configuration to pyproject.toml
  • Build system: initial support for NVIDIA Blackwell B100 GPUs, RTX 50 Blackwell series GPUs and Jetson Thor Blackwell.

    • Note: Binaries built for these platforms are not included in this release. They will be included in future releases upon the availability of the upcoming CUDA Toolkit 12.7 and 12.8.
Bug Fixes:
  • Packaging: wheels will no longer include unit tests. (#1478)
Dependencies:
  • Sets the minimum PyTorch version to 2.0.0.
0.45.0
This is a significant release, bringing support for LLM.int8() to NVIDIA Hopper GPUs such as the H100.
As part of the compatibility enhancements, we've rebuilt much of the LLM.int8() code in order to simplify for future compatibility and maintenance. We no longer use the col32 or architecture-specific tensor layout formats while maintaining backwards compatibility. We additionally bring performance improvements targeted for inference scenarios.
Performance Improvements
This release includes broad performance improvements for a wide variety of inference scenarios. See this X thread for a detailed explanation.
Breaking Changes
🤗PEFT users wishing to merge adapters with 8-bit weights will need to upgrade to peft>=0.14.0.
Packaging Improvements
  • The size of our wheel has been reduced by ~43.5% from 122.4 MB to 69.1 MB! This results in an on-disk size decrease from ~396MB to ~224MB.
  • Binaries built with CUDA Toolkit 12.6.2 are now included in the PyPI distribution.
  • The CUDA 12.5.0 build has been updated to CUDA Toolkit 12.5.1.
Deprecations
  • A number of public API functions have been marked for deprecation and will emit FutureWarning when used. These functions will become unavailable in future releases. This should have minimal impact on most end-users.
  • The k-bit quantization features are deprecated in favor of blockwise quantization. For all optimizers, using block_wise=False is not recommended and support will be removed in a future release.
  • As part of the refactoring process, we've implemented many new 8bit operations. These operations no longer use specialized data layouts.
Full Changelog
0.44.1
Bug fixes:
... (truncated)
Commits
  • 37d2a93 Release 0.50.1
  • 0b3a226 Add sm121 (GB10) tier to the 4-bit GEMM dispatch heuristic
  • 557bfc2 build: Add Windows ARM64 build with CUDA 13.4 for RTX Spark (#2038)
  • 930274c Merge pull request #2032 from mfuntowicz/fix/cuda_121_win
  • 0330f40 Merge branch 'main' into fix/cuda_121_win
  • d799cfd Gate /Zc:preprocessor to cl.exe only
  • 915aa03 Merge pull request #2037 from mfuntowicz/docs/rtx-spark-install-guidelines
  • cf86065 docs: add installation instructions for NVIDIA Spark (ARM64) devices
  • b459659 fix: missing compilation flag on recent msvc version
  • a2b90e6 Fix truncated FP4 constant in Triton dequantize_fp4_tree (#2026)
  • Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.
Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR:
  • @dependabot rebase will rebase this PR
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  • @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
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@dependabot
chore(deps): update bitsandbytes requirement in /fowoco-knowledge
7987916
Updates the requirements on [bitsandbytes](https://github.com/bitsandbytes-foundation/bitsandbytes) to permit the latest version.
- [Release notes](https://github.com/bitsandbytes-foundation/bitsandbytes/releases)
- [Changelog](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/main/CHANGELOG.md)
- [Commits](bitsandbytes-foundation/bitsandbytes@0.44.0...0.50.1)
---
updated-dependencies:
- dependency-name: bitsandbytes
dependency-version: 0.50.1
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
@dependabotdependabotBot
added

area:knowledge
Context Pack·Workflow·공식 출처 관리
priority:P2
일정에 따라 미룰 수 있는 보완 작업
type:chore
유지보수·저장소 설정 작업
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Aug 24, 2026
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, 'i');
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})();
(function(){
try {
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var __re = new RegExp('^' + ".*" + '

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chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge - #68
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chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge#68
dependabot[bot] wants to merge 1 commit into
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Updates the requirements on bitsandbytes to permit the latest version.
Release notes
Sourced from bitsandbytes's releases.
0.50.1: RTX Spark Support
This release adds support for additional hardware platforms and improves performance on RTX Spark / DGX Spark.
Highlights
  • Support added for NVIDIA RTX Spark products running Windows on ARM64 (#2038, #2037, #2032)
  • Improved 4bit GEMM dispatch heuristics for NVIDIA GB10 (#2030)
  • Support for AMD CDNA5 hardware (e.g. MI455X)
What's Changed
New Contributors
Full Changelog: bitsandbytes-foundation/bitsandbytes@0.50.0...0.50.1
Changelog
Sourced from bitsandbytes's changelog.
v0.45.1
Improvements:
  • Compatibility for triton>=3.2.0
  • Moved package configuration to pyproject.toml
  • Build system: initial support for NVIDIA Blackwell B100 GPUs, RTX 50 Blackwell series GPUs and Jetson Thor Blackwell.

    • Note: Binaries built for these platforms are not included in this release. They will be included in future releases upon the availability of the upcoming CUDA Toolkit 12.7 and 12.8.
Bug Fixes:
  • Packaging: wheels will no longer include unit tests. (#1478)
Dependencies:
  • Sets the minimum PyTorch version to 2.0.0.
0.45.0
This is a significant release, bringing support for LLM.int8() to NVIDIA Hopper GPUs such as the H100.
As part of the compatibility enhancements, we've rebuilt much of the LLM.int8() code in order to simplify for future compatibility and maintenance. We no longer use the col32 or architecture-specific tensor layout formats while maintaining backwards compatibility. We additionally bring performance improvements targeted for inference scenarios.
Performance Improvements
This release includes broad performance improvements for a wide variety of inference scenarios. See this X thread for a detailed explanation.
Breaking Changes
🤗PEFT users wishing to merge adapters with 8-bit weights will need to upgrade to peft>=0.14.0.
Packaging Improvements
  • The size of our wheel has been reduced by ~43.5% from 122.4 MB to 69.1 MB! This results in an on-disk size decrease from ~396MB to ~224MB.
  • Binaries built with CUDA Toolkit 12.6.2 are now included in the PyPI distribution.
  • The CUDA 12.5.0 build has been updated to CUDA Toolkit 12.5.1.
Deprecations
  • A number of public API functions have been marked for deprecation and will emit FutureWarning when used. These functions will become unavailable in future releases. This should have minimal impact on most end-users.
  • The k-bit quantization features are deprecated in favor of blockwise quantization. For all optimizers, using block_wise=False is not recommended and support will be removed in a future release.
  • As part of the refactoring process, we've implemented many new 8bit operations. These operations no longer use specialized data layouts.
Full Changelog
0.44.1
Bug fixes:
... (truncated)
Commits
  • 37d2a93 Release 0.50.1
  • 0b3a226 Add sm121 (GB10) tier to the 4-bit GEMM dispatch heuristic
  • 557bfc2 build: Add Windows ARM64 build with CUDA 13.4 for RTX Spark (#2038)
  • 930274c Merge pull request #2032 from mfuntowicz/fix/cuda_121_win
  • 0330f40 Merge branch 'main' into fix/cuda_121_win
  • d799cfd Gate /Zc:preprocessor to cl.exe only
  • 915aa03 Merge pull request #2037 from mfuntowicz/docs/rtx-spark-install-guidelines
  • cf86065 docs: add installation instructions for NVIDIA Spark (ARM64) devices
  • b459659 fix: missing compilation flag on recent msvc version
  • a2b90e6 Fix truncated FP4 constant in Triton dequantize_fp4_tree (#2026)
  • Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.
Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR:
  • @dependabot rebase will rebase this PR
  • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
  • @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
  • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
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@dependabot
chore(deps): update bitsandbytes requirement in /fowoco-knowledge
7987916
Updates the requirements on [bitsandbytes](https://github.com/bitsandbytes-foundation/bitsandbytes) to permit the latest version.
- [Release notes](https://github.com/bitsandbytes-foundation/bitsandbytes/releases)
- [Changelog](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/main/CHANGELOG.md)
- [Commits](bitsandbytes-foundation/bitsandbytes@0.44.0...0.50.1)
---
updated-dependencies:
- dependency-name: bitsandbytes
dependency-version: 0.50.1
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
@dependabotdependabotBot
added

area:knowledge
Context Pack·Workflow·공식 출처 관리
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type:chore
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, 'i');
if (__m === '*' || __re.test(location.href)) {
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(function(){
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var __m = "*";
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chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge - #68
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chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge#68
dependabot[bot] wants to merge 1 commit into
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commented
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Updates the requirements on bitsandbytes to permit the latest version.
Release notes
Sourced from bitsandbytes's releases.
0.50.1: RTX Spark Support
This release adds support for additional hardware platforms and improves performance on RTX Spark / DGX Spark.
Highlights
  • Support added for NVIDIA RTX Spark products running Windows on ARM64 (#2038, #2037, #2032)
  • Improved 4bit GEMM dispatch heuristics for NVIDIA GB10 (#2030)
  • Support for AMD CDNA5 hardware (e.g. MI455X)
What's Changed
New Contributors
Full Changelog: bitsandbytes-foundation/bitsandbytes@0.50.0...0.50.1
Changelog
Sourced from bitsandbytes's changelog.
v0.45.1
Improvements:
  • Compatibility for triton>=3.2.0
  • Moved package configuration to pyproject.toml
  • Build system: initial support for NVIDIA Blackwell B100 GPUs, RTX 50 Blackwell series GPUs and Jetson Thor Blackwell.

    • Note: Binaries built for these platforms are not included in this release. They will be included in future releases upon the availability of the upcoming CUDA Toolkit 12.7 and 12.8.
Bug Fixes:
  • Packaging: wheels will no longer include unit tests. (#1478)
Dependencies:
  • Sets the minimum PyTorch version to 2.0.0.
0.45.0
This is a significant release, bringing support for LLM.int8() to NVIDIA Hopper GPUs such as the H100.
As part of the compatibility enhancements, we've rebuilt much of the LLM.int8() code in order to simplify for future compatibility and maintenance. We no longer use the col32 or architecture-specific tensor layout formats while maintaining backwards compatibility. We additionally bring performance improvements targeted for inference scenarios.
Performance Improvements
This release includes broad performance improvements for a wide variety of inference scenarios. See this X thread for a detailed explanation.
Breaking Changes
🤗PEFT users wishing to merge adapters with 8-bit weights will need to upgrade to peft>=0.14.0.
Packaging Improvements
  • The size of our wheel has been reduced by ~43.5% from 122.4 MB to 69.1 MB! This results in an on-disk size decrease from ~396MB to ~224MB.
  • Binaries built with CUDA Toolkit 12.6.2 are now included in the PyPI distribution.
  • The CUDA 12.5.0 build has been updated to CUDA Toolkit 12.5.1.
Deprecations
  • A number of public API functions have been marked for deprecation and will emit FutureWarning when used. These functions will become unavailable in future releases. This should have minimal impact on most end-users.
  • The k-bit quantization features are deprecated in favor of blockwise quantization. For all optimizers, using block_wise=False is not recommended and support will be removed in a future release.
  • As part of the refactoring process, we've implemented many new 8bit operations. These operations no longer use specialized data layouts.
Full Changelog
0.44.1
Bug fixes:
... (truncated)
Commits
  • 37d2a93 Release 0.50.1
  • 0b3a226 Add sm121 (GB10) tier to the 4-bit GEMM dispatch heuristic
  • 557bfc2 build: Add Windows ARM64 build with CUDA 13.4 for RTX Spark (#2038)
  • 930274c Merge pull request #2032 from mfuntowicz/fix/cuda_121_win
  • 0330f40 Merge branch 'main' into fix/cuda_121_win
  • d799cfd Gate /Zc:preprocessor to cl.exe only
  • 915aa03 Merge pull request #2037 from mfuntowicz/docs/rtx-spark-install-guidelines
  • cf86065 docs: add installation instructions for NVIDIA Spark (ARM64) devices
  • b459659 fix: missing compilation flag on recent msvc version
  • a2b90e6 Fix truncated FP4 constant in Triton dequantize_fp4_tree (#2026)
  • Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.
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@dependabot
chore(deps): update bitsandbytes requirement in /fowoco-knowledge
7987916
Updates the requirements on [bitsandbytes](https://github.com/bitsandbytes-foundation/bitsandbytes) to permit the latest version.
- [Release notes](https://github.com/bitsandbytes-foundation/bitsandbytes/releases)
- [Changelog](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/main/CHANGELOG.md)
- [Commits](bitsandbytes-foundation/bitsandbytes@0.44.0...0.50.1)
---
updated-dependencies:
- dependency-name: bitsandbytes
dependency-version: 0.50.1
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
@dependabotdependabotBot
added

area:knowledge
Context Pack·Workflow·공식 출처 관리
priority:P2
일정에 따라 미룰 수 있는 보완 작업
type:chore
유지보수·저장소 설정 작업
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge - #68
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chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge#68
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Updates the requirements on bitsandbytes to permit the latest version.
Release notes
Sourced from bitsandbytes's releases.
0.50.1: RTX Spark Support
This release adds support for additional hardware platforms and improves performance on RTX Spark / DGX Spark.
Highlights
  • Support added for NVIDIA RTX Spark products running Windows on ARM64 (#2038, #2037, #2032)
  • Improved 4bit GEMM dispatch heuristics for NVIDIA GB10 (#2030)
  • Support for AMD CDNA5 hardware (e.g. MI455X)
What's Changed
New Contributors
Full Changelog: bitsandbytes-foundation/bitsandbytes@0.50.0...0.50.1
Changelog
Sourced from bitsandbytes's changelog.
v0.45.1
Improvements:
  • Compatibility for triton>=3.2.0
  • Moved package configuration to pyproject.toml
  • Build system: initial support for NVIDIA Blackwell B100 GPUs, RTX 50 Blackwell series GPUs and Jetson Thor Blackwell.

    • Note: Binaries built for these platforms are not included in this release. They will be included in future releases upon the availability of the upcoming CUDA Toolkit 12.7 and 12.8.
Bug Fixes:
  • Packaging: wheels will no longer include unit tests. (#1478)
Dependencies:
  • Sets the minimum PyTorch version to 2.0.0.
0.45.0
This is a significant release, bringing support for LLM.int8() to NVIDIA Hopper GPUs such as the H100.
As part of the compatibility enhancements, we've rebuilt much of the LLM.int8() code in order to simplify for future compatibility and maintenance. We no longer use the col32 or architecture-specific tensor layout formats while maintaining backwards compatibility. We additionally bring performance improvements targeted for inference scenarios.
Performance Improvements
This release includes broad performance improvements for a wide variety of inference scenarios. See this X thread for a detailed explanation.
Breaking Changes
🤗PEFT users wishing to merge adapters with 8-bit weights will need to upgrade to peft>=0.14.0.
Packaging Improvements
  • The size of our wheel has been reduced by ~43.5% from 122.4 MB to 69.1 MB! This results in an on-disk size decrease from ~396MB to ~224MB.
  • Binaries built with CUDA Toolkit 12.6.2 are now included in the PyPI distribution.
  • The CUDA 12.5.0 build has been updated to CUDA Toolkit 12.5.1.
Deprecations
  • A number of public API functions have been marked for deprecation and will emit FutureWarning when used. These functions will become unavailable in future releases. This should have minimal impact on most end-users.
  • The k-bit quantization features are deprecated in favor of blockwise quantization. For all optimizers, using block_wise=False is not recommended and support will be removed in a future release.
  • As part of the refactoring process, we've implemented many new 8bit operations. These operations no longer use specialized data layouts.
Full Changelog
0.44.1
Bug fixes:
... (truncated)
Commits
  • 37d2a93 Release 0.50.1
  • 0b3a226 Add sm121 (GB10) tier to the 4-bit GEMM dispatch heuristic
  • 557bfc2 build: Add Windows ARM64 build with CUDA 13.4 for RTX Spark (#2038)
  • 930274c Merge pull request #2032 from mfuntowicz/fix/cuda_121_win
  • 0330f40 Merge branch 'main' into fix/cuda_121_win
  • d799cfd Gate /Zc:preprocessor to cl.exe only
  • 915aa03 Merge pull request #2037 from mfuntowicz/docs/rtx-spark-install-guidelines
  • cf86065 docs: add installation instructions for NVIDIA Spark (ARM64) devices
  • b459659 fix: missing compilation flag on recent msvc version
  • a2b90e6 Fix truncated FP4 constant in Triton dequantize_fp4_tree (#2026)
  • Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.
Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR:
  • @dependabot rebase will rebase this PR
  • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
  • @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
  • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
@dependabot
chore(deps): update bitsandbytes requirement in /fowoco-knowledge
7987916
Updates the requirements on [bitsandbytes](https://github.com/bitsandbytes-foundation/bitsandbytes) to permit the latest version.
- [Release notes](https://github.com/bitsandbytes-foundation/bitsandbytes/releases)
- [Changelog](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/main/CHANGELOG.md)
- [Commits](bitsandbytes-foundation/bitsandbytes@0.44.0...0.50.1)
---
updated-dependencies:
- dependency-name: bitsandbytes
dependency-version: 0.50.1
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
@dependabotdependabotBot
added

area:knowledge
Context Pack·Workflow·공식 출처 관리
priority:P2
일정에 따라 미룰 수 있는 보완 작업
type:chore
유지보수·저장소 설정 작업
labels
Aug 24, 2026
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge - #68
Open
dependabot[bot] wants to merge 1 commit into
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dependabot/pip/fowoco-knowledge/bitsandbytes-gte-0.50.1-and-lt-1
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chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge#68
dependabot[bot] wants to merge 1 commit into
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Conversation
@dependabot
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commented
on behalf of githubAug 24, 2026

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Contributor
Updates the requirements on bitsandbytes to permit the latest version.
Release notes
Sourced from bitsandbytes's releases.
0.50.1: RTX Spark Support
This release adds support for additional hardware platforms and improves performance on RTX Spark / DGX Spark.
Highlights
  • Support added for NVIDIA RTX Spark products running Windows on ARM64 (#2038, #2037, #2032)
  • Improved 4bit GEMM dispatch heuristics for NVIDIA GB10 (#2030)
  • Support for AMD CDNA5 hardware (e.g. MI455X)
What's Changed
New Contributors
Full Changelog: bitsandbytes-foundation/bitsandbytes@0.50.0...0.50.1
Changelog
Sourced from bitsandbytes's changelog.
v0.45.1
Improvements:
  • Compatibility for triton>=3.2.0
  • Moved package configuration to pyproject.toml
  • Build system: initial support for NVIDIA Blackwell B100 GPUs, RTX 50 Blackwell series GPUs and Jetson Thor Blackwell.

    • Note: Binaries built for these platforms are not included in this release. They will be included in future releases upon the availability of the upcoming CUDA Toolkit 12.7 and 12.8.
Bug Fixes:
  • Packaging: wheels will no longer include unit tests. (#1478)
Dependencies:
  • Sets the minimum PyTorch version to 2.0.0.
0.45.0
This is a significant release, bringing support for LLM.int8() to NVIDIA Hopper GPUs such as the H100.
As part of the compatibility enhancements, we've rebuilt much of the LLM.int8() code in order to simplify for future compatibility and maintenance. We no longer use the col32 or architecture-specific tensor layout formats while maintaining backwards compatibility. We additionally bring performance improvements targeted for inference scenarios.
Performance Improvements
This release includes broad performance improvements for a wide variety of inference scenarios. See this X thread for a detailed explanation.
Breaking Changes
🤗PEFT users wishing to merge adapters with 8-bit weights will need to upgrade to peft>=0.14.0.
Packaging Improvements
  • The size of our wheel has been reduced by ~43.5% from 122.4 MB to 69.1 MB! This results in an on-disk size decrease from ~396MB to ~224MB.
  • Binaries built with CUDA Toolkit 12.6.2 are now included in the PyPI distribution.
  • The CUDA 12.5.0 build has been updated to CUDA Toolkit 12.5.1.
Deprecations
  • A number of public API functions have been marked for deprecation and will emit FutureWarning when used. These functions will become unavailable in future releases. This should have minimal impact on most end-users.
  • The k-bit quantization features are deprecated in favor of blockwise quantization. For all optimizers, using block_wise=False is not recommended and support will be removed in a future release.
  • As part of the refactoring process, we've implemented many new 8bit operations. These operations no longer use specialized data layouts.
Full Changelog
0.44.1
Bug fixes:
... (truncated)
Commits
  • 37d2a93 Release 0.50.1
  • 0b3a226 Add sm121 (GB10) tier to the 4-bit GEMM dispatch heuristic
  • 557bfc2 build: Add Windows ARM64 build with CUDA 13.4 for RTX Spark (#2038)
  • 930274c Merge pull request #2032 from mfuntowicz/fix/cuda_121_win
  • 0330f40 Merge branch 'main' into fix/cuda_121_win
  • d799cfd Gate /Zc:preprocessor to cl.exe only
  • 915aa03 Merge pull request #2037 from mfuntowicz/docs/rtx-spark-install-guidelines
  • cf86065 docs: add installation instructions for NVIDIA Spark (ARM64) devices
  • b459659 fix: missing compilation flag on recent msvc version
  • a2b90e6 Fix truncated FP4 constant in Triton dequantize_fp4_tree (#2026)
  • Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.
Dependabot commands and options
You can trigger Dependabot actions by commenting on this PR:
  • @dependabot rebase will rebase this PR
  • @dependabot recreate will recreate this PR, overwriting any edits that have been made to it
  • @dependabot show <dependency name> ignore conditions will show all of the ignore conditions of the specified dependency
  • @dependabot ignore this major version will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this minor version will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself)
  • @dependabot ignore this dependency will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself)
@dependabot
chore(deps): update bitsandbytes requirement in /fowoco-knowledge
7987916
Updates the requirements on [bitsandbytes](https://github.com/bitsandbytes-foundation/bitsandbytes) to permit the latest version.
- [Release notes](https://github.com/bitsandbytes-foundation/bitsandbytes/releases)
- [Changelog](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/main/CHANGELOG.md)
- [Commits](bitsandbytes-foundation/bitsandbytes@0.44.0...0.50.1)
---
updated-dependencies:
- dependency-name: bitsandbytes
dependency-version: 0.50.1
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
@dependabotdependabotBot
added

area:knowledge
Context Pack·Workflow·공식 출처 관리
priority:P2
일정에 따라 미룰 수 있는 보완 작업
type:chore
유지보수·저장소 설정 작업
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge - #68
Open
dependabot[bot] wants to merge 1 commit into
mainfrom 
dependabot/pip/fowoco-knowledge/bitsandbytes-gte-0.50.1-and-lt-1
Open
chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge#68
dependabot[bot] wants to merge 1 commit into
mainfrom 
dependabot/pip/fowoco-knowledge/bitsandbytes-gte-0.50.1-and-lt-1
Conversation
@dependabot
@dependabotdependabotBot
commented
on behalf of githubAug 24, 2026

Copy link


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Contributor
Updates the requirements on bitsandbytes to permit the latest version.
Release notes
Sourced from bitsandbytes's releases.
0.50.1: RTX Spark Support
This release adds support for additional hardware platforms and improves performance on RTX Spark / DGX Spark.
Highlights
  • Support added for NVIDIA RTX Spark products running Windows on ARM64 (#2038, #2037, #2032)
  • Improved 4bit GEMM dispatch heuristics for NVIDIA GB10 (#2030)
  • Support for AMD CDNA5 hardware (e.g. MI455X)
What's Changed
New Contributors
Full Changelog: bitsandbytes-foundation/bitsandbytes@0.50.0...0.50.1
Changelog
Sourced from bitsandbytes's changelog.
v0.45.1
Improvements:
  • Compatibility for triton>=3.2.0
  • Moved package configuration to pyproject.toml
  • Build system: initial support for NVIDIA Blackwell B100 GPUs, RTX 50 Blackwell series GPUs and Jetson Thor Blackwell.

    • Note: Binaries built for these platforms are not included in this release. They will be included in future releases upon the availability of the upcoming CUDA Toolkit 12.7 and 12.8.
Bug Fixes:
  • Packaging: wheels will no longer include unit tests. (#1478)
Dependencies:
  • Sets the minimum PyTorch version to 2.0.0.
0.45.0
This is a significant release, bringing support for LLM.int8() to NVIDIA Hopper GPUs such as the H100.
As part of the compatibility enhancements, we've rebuilt much of the LLM.int8() code in order to simplify for future compatibility and maintenance. We no longer use the col32 or architecture-specific tensor layout formats while maintaining backwards compatibility. We additionally bring performance improvements targeted for inference scenarios.
Performance Improvements
This release includes broad performance improvements for a wide variety of inference scenarios. See this X thread for a detailed explanation.
Breaking Changes
🤗PEFT users wishing to merge adapters with 8-bit weights will need to upgrade to peft>=0.14.0.
Packaging Improvements
  • The size of our wheel has been reduced by ~43.5% from 122.4 MB to 69.1 MB! This results in an on-disk size decrease from ~396MB to ~224MB.
  • Binaries built with CUDA Toolkit 12.6.2 are now included in the PyPI distribution.
  • The CUDA 12.5.0 build has been updated to CUDA Toolkit 12.5.1.
Deprecations
  • A number of public API functions have been marked for deprecation and will emit FutureWarning when used. These functions will become unavailable in future releases. This should have minimal impact on most end-users.
  • The k-bit quantization features are deprecated in favor of blockwise quantization. For all optimizers, using block_wise=False is not recommended and support will be removed in a future release.
  • As part of the refactoring process, we've implemented many new 8bit operations. These operations no longer use specialized data layouts.
Full Changelog
0.44.1
Bug fixes:
... (truncated)
Commits
  • 37d2a93 Release 0.50.1
  • 0b3a226 Add sm121 (GB10) tier to the 4-bit GEMM dispatch heuristic
  • 557bfc2 build: Add Windows ARM64 build with CUDA 13.4 for RTX Spark (#2038)
  • 930274c Merge pull request #2032 from mfuntowicz/fix/cuda_121_win
  • 0330f40 Merge branch 'main' into fix/cuda_121_win
  • d799cfd Gate /Zc:preprocessor to cl.exe only
  • 915aa03 Merge pull request #2037 from mfuntowicz/docs/rtx-spark-install-guidelines
  • cf86065 docs: add installation instructions for NVIDIA Spark (ARM64) devices
  • b459659 fix: missing compilation flag on recent msvc version
  • a2b90e6 Fix truncated FP4 constant in Triton dequantize_fp4_tree (#2026)
  • Additional commits viewable in compare view

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chore(deps): update bitsandbytes requirement in /fowoco-knowledge
7987916
Updates the requirements on [bitsandbytes](https://github.com/bitsandbytes-foundation/bitsandbytes) to permit the latest version.
- [Release notes](https://github.com/bitsandbytes-foundation/bitsandbytes/releases)
- [Changelog](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/main/CHANGELOG.md)
- [Commits](bitsandbytes-foundation/bitsandbytes@0.44.0...0.50.1)
---
updated-dependencies:
- dependency-name: bitsandbytes
dependency-version: 0.50.1
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
@dependabotdependabotBot
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Aug 24, 2026
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, 'i');
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}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge - #68
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chore(deps): update bitsandbytes requirement from <1,>=0.44 to >=0.50.1,<1 in /fowoco-knowledge#68
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Updates the requirements on bitsandbytes to permit the latest version.
Release notes
Sourced from bitsandbytes's releases.
0.50.1: RTX Spark Support
This release adds support for additional hardware platforms and improves performance on RTX Spark / DGX Spark.
Highlights
  • Support added for NVIDIA RTX Spark products running Windows on ARM64 (#2038, #2037, #2032)
  • Improved 4bit GEMM dispatch heuristics for NVIDIA GB10 (#2030)
  • Support for AMD CDNA5 hardware (e.g. MI455X)
What's Changed
New Contributors
Full Changelog: bitsandbytes-foundation/bitsandbytes@0.50.0...0.50.1
Changelog
Sourced from bitsandbytes's changelog.
v0.45.1
Improvements:
  • Compatibility for triton>=3.2.0
  • Moved package configuration to pyproject.toml
  • Build system: initial support for NVIDIA Blackwell B100 GPUs, RTX 50 Blackwell series GPUs and Jetson Thor Blackwell.

    • Note: Binaries built for these platforms are not included in this release. They will be included in future releases upon the availability of the upcoming CUDA Toolkit 12.7 and 12.8.
Bug Fixes:
  • Packaging: wheels will no longer include unit tests. (#1478)
Dependencies:
  • Sets the minimum PyTorch version to 2.0.0.
0.45.0
This is a significant release, bringing support for LLM.int8() to NVIDIA Hopper GPUs such as the H100.
As part of the compatibility enhancements, we've rebuilt much of the LLM.int8() code in order to simplify for future compatibility and maintenance. We no longer use the col32 or architecture-specific tensor layout formats while maintaining backwards compatibility. We additionally bring performance improvements targeted for inference scenarios.
Performance Improvements
This release includes broad performance improvements for a wide variety of inference scenarios. See this X thread for a detailed explanation.
Breaking Changes
🤗PEFT users wishing to merge adapters with 8-bit weights will need to upgrade to peft>=0.14.0.
Packaging Improvements
  • The size of our wheel has been reduced by ~43.5% from 122.4 MB to 69.1 MB! This results in an on-disk size decrease from ~396MB to ~224MB.
  • Binaries built with CUDA Toolkit 12.6.2 are now included in the PyPI distribution.
  • The CUDA 12.5.0 build has been updated to CUDA Toolkit 12.5.1.
Deprecations
  • A number of public API functions have been marked for deprecation and will emit FutureWarning when used. These functions will become unavailable in future releases. This should have minimal impact on most end-users.
  • The k-bit quantization features are deprecated in favor of blockwise quantization. For all optimizers, using block_wise=False is not recommended and support will be removed in a future release.
  • As part of the refactoring process, we've implemented many new 8bit operations. These operations no longer use specialized data layouts.
Full Changelog
0.44.1
Bug fixes:
... (truncated)
Commits
  • 37d2a93 Release 0.50.1
  • 0b3a226 Add sm121 (GB10) tier to the 4-bit GEMM dispatch heuristic
  • 557bfc2 build: Add Windows ARM64 build with CUDA 13.4 for RTX Spark (#2038)
  • 930274c Merge pull request #2032 from mfuntowicz/fix/cuda_121_win
  • 0330f40 Merge branch 'main' into fix/cuda_121_win
  • d799cfd Gate /Zc:preprocessor to cl.exe only
  • 915aa03 Merge pull request #2037 from mfuntowicz/docs/rtx-spark-install-guidelines
  • cf86065 docs: add installation instructions for NVIDIA Spark (ARM64) devices
  • b459659 fix: missing compilation flag on recent msvc version
  • a2b90e6 Fix truncated FP4 constant in Triton dequantize_fp4_tree (#2026)
  • Additional commits viewable in compare view

Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting @dependabot rebase.
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@dependabot
chore(deps): update bitsandbytes requirement in /fowoco-knowledge
7987916
Updates the requirements on [bitsandbytes](https://github.com/bitsandbytes-foundation/bitsandbytes) to permit the latest version.
- [Release notes](https://github.com/bitsandbytes-foundation/bitsandbytes/releases)
- [Changelog](https://github.com/bitsandbytes-foundation/bitsandbytes/blob/main/CHANGELOG.md)
- [Commits](bitsandbytes-foundation/bitsandbytes@0.44.0...0.50.1)
---
updated-dependencies:
- dependency-name: bitsandbytes
dependency-version: 0.50.1
dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
@dependabotdependabotBot
added

area:knowledge
Context Pack·Workflow·공식 출처 관리
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일정에 따라 미룰 수 있는 보완 작업
type:chore
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Aug 24, 2026
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