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@PierreGtch PierreGtch released this 28 May 21:30
v0.5.0
e99fb3c
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Learn about vigilant mode.

Added

  • Add a required revision field on Dataset (forwarded to BaseConcatDataset.pull_from_hub) and pin every default dataset config to its current HuggingFace commit SHA for reproducibility (#37).
  • Add training_required_parameters field on _BackboneBase for top-level nn.Parameter names that must remain trainable (e.g. Labram's temporal_embedding). Distinct from training_required_modules, which only accepts nn.Module names. Finetuning methods declare compatibility via the supports_training_required_parameters class variable; IA3 and OFT opt out. LoRA/AdaLoRA/DoRA forward the list to PEFT's target_parameters; Frozen/TwoStages extend their unfreeze list (#25).

Changed

  • Allow custom normalization methods by subclassing Normalization, now based on exca.helpers.DiscriminatedModel. Builtin subclasses pin their pre-existing kind value to preserve cached experiment UIDs (#35).

Full Changelog: v0.4.0...v0.5.0

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