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SparseML v0.10.0
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@jeanniefinks jeanniefinks released this 03 Feb 16:38
· 1 commit to release/0.10 since this release
v0.10.0
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Learn about vigilant mode.

New Features:

  • Hugging Face Transformers native integration and CLIs implemented for installation to train transformer models.
  • Cyclic LR support added to LearningRateFunctionModifier in PyTorch.
  • ViT (vision transformer) examples added with the rwightman/timm integration.

Changes:

  • Quantization implementation for BERT models improved (shorter schedules and better recovery).
  • PyTorch image classification script saves based on top 1 accuracy now instead of loss.
  • Integration rwightman/timm updated for ease-of-use with setup_integration.sh to set up the environment properly.

Resolved Issues:

  • Github actions now triggering for external forks.

Known Issues:

  • Conversion of quantized Hugging Face BERT models from PyTorch to ONNX is currently dropping accuracy, ranging from 1-25% depending on the task and dataset. A hotfix is being pursued; users can fall back to version 0.9.0 to prevent the issue.
  • Export for masked language modeling with Hugging Face BERT models from PyTorch is currently exporting incorrectly due to a configuration issue. A hotfix is being pursued; users can fall back to version 0.9.0 to prevent the issue.
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