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hyperonym / basaran

Basaran is an open-source alternative to the OpenAI text completion API. It provides a compatible streaming API for your Hugging Face Transformers-based text generation models.
MIT License
1.29k stars 80 forks source link

build(deps): update bitsandbytes requirement from ~=0.37.2 to ~=0.38.0 #119

Closed dependabot[bot] closed 1 year ago

dependabot[bot] commented 1 year ago

Updates the requirements on bitsandbytes to permit the latest version.

Changelog

Sourced from bitsandbytes's changelog.

0.0.21

  • Ampere, RTX 30 series GPUs now compatible with the library.

0.0.22:

  • Fixed an error where a reset_parameters() call on the StableEmbedding would lead to an error in older PyTorch versions (from 1.7.0).

0.0.23:

Bugs:

  • Unified quantization API: each quantization function now returns Q, S where Q is the quantized tensor and S the quantization state which may hold absolute max values, a quantization map or more. For dequantization all functions now accept the inputs Q, S so that Q is dequantized with the quantization state S.
  • Fixed an issue where the CUDA 11.1 binary was not compiled with the right headers

API changes:

  • Block-wise quantization for optimizers now enabled by default

Features:

  • Block-wise quantization routines now support CPU Tensors.

0.0.24:

  • Fixed a bug where a float/half conversion led to a compilation error for CUDA 11.1 on Turning GPUs.
  • removed Apex dependency for bnb LAMB

0.0.25:

Features:

  • Added skip_zeros for block-wise and 32-bit optimizers. This ensures correct updates for sparse gradients and sparse models.
  • Added support for Kepler GPUs. (#4)
  • Added Analysis Adam to track 8-bit vs 32-bit quantization errors over time.
  • Make compilation more user friendly.

Bug fixes:

  • fixed "undefined symbol: __fatbinwrap_38" error for P100 GPUs on CUDA 10.1 (#5)

Docs:

  • Added docs with instructions to compile from source.

0.26.0:

Features:

  • Added Adagrad (without grad clipping) as 32-bit and 8-bit block-wise optimizer.
  • Added AdamW (copy of Adam with weight decay init 1e-2). #10
  • Introduced ModuleConfig overrides which can be seamlessly be used at initialization time of a module.
  • Added bnb.nn.Embedding layer which runs at 32-bit but without the layernorm. This works well if you need to fine-tune pretrained models that do not have a embedding layer norm. #19

Bug fixes:

  • Fixed a bug where weight decay was incorrectly applied to 32-bit Adam. #13

... (truncated)

Commits


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codecov-commenter commented 1 year ago

Codecov Report

Patch and project coverage have no change.

Comparison is base (5c3ead1) 94.23% compared to head (9e7c4af) 94.23%.

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