This release comes with two main features:

• A DistillationSetFitTrainer class that allows users to use unlabeled data to significantly boost the performance of small models like MiniLM. See this workshop for an end-to-end example.
• An ONNX exporter that converts the SetFit model instances into ONNX graphs for downstream inference + optimisation. Checkout the notebooks folder for an end-to-end example.

Kudos to @orenpereg and @nbertagnolli for implementing both of these features 🔥

Bug fixes and improvements

• Tidy up Makefile & create notebook table by @lewtun in #163
• Fix by @lewtun in #164
• Fixed typo in model head from predict_prob to predict_proba by @nbertagnolli in #171
• Distill trainer by @orenpereg in #166
• Update evaluate by @lvwerra in #194
• Use scikit-learn rather than sklearn in requirements files by @lesteve in #200
• Bugfix/body and head on different devices by @blakechi in #175
• add option to normalize embeddings by @PhilipMay in #177
• delete duplicated code by @Yongtae723 in #183
• Throw clear ValueError when neglecting to pass train_dataset to DistillationSetFitTrainer by @tomaarsen in #190
• add option to set samples_per_label by @PhilipMay in #196
• Resolve typo: sklean -> sklearn, #220 by @tomaarsen in #221
• Allow setting max length by @blakechi in #176
• add doc for num_iterations by @PhilipMay in #215
• Allow training progress bars to be disabled by @tomaarsen in #218
• Added initial onnx export function by @nbertagnolli in #156
• Fix/input type hint by @Yongtae723 in #184
• fixed spell errors in code example by @Gladiator07 in #210
• For scripts/setfit/run_fewshot.py, add warning for class imbalance w. accuracy by @tomaarsen in #204
• No longer needlessly deepcopy the original model state by @tomaarsen in #201
• Various cleanups; type hint fixes incl. corresponding to PEP 484 by @tomaarsen in #185
• Expand CI tests using matrix; make dependencies less restrictive; fix ONNX tests by @tomaarsen in #233
• Add SetFitModel.to by @jegork in #229
• Revert "Add SetFitModel.to by @lewtun in #229)"

Significant community contributions

The following contributors have made significant changes to the library over the last release:

• @nbertagnolli
  • Fixed typo in model head from predict_prob to predict_proba (#171)
  • Added initial onnx export function (#156)
• @orenpereg
  • Distill trainer (#166)