Update dependency bitsandbytes to v0.45.1 (rhoai-2.16) - abandoned - autoclosed

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This PR contains the following updates:

Package	Update	Change
bitsandbytes (changelog)	minor	==0.44.1 -> ==0.45.1

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Release Notes

bitsandbytes-foundation/bitsandbytes (bitsandbytes)

v0.45.1

Compare Source

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.

v0.45.0

Compare Source

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

• refine docs for multi-backend alpha release by @​Titus-von-Koeller in #​1380
• README: Replace special Unicode text symbols with regular characters by @​akx in #​1385
• Update CI tools & fix typos by @​akx in #​1386
• Fix invalid escape sequence warning in Python 3.12 by @​oshiteku in #​1420
• [Build] Add CUDA 12.6.2 build; update 12.5.0 to 12.5.1 by @​matthewdouglas in #​1431
• LLM.int8() Refactoring: Part 1 by @​matthewdouglas in #​1401

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