- NERDA model class is now equipped with functions for saving (loading) weights for a fine-tuned NERDA Network to (from) file. See functions model.save_network() and model.load_network_from_file()
- return confidence scores for predictions of all tokens, e.g. model.predict(x, return_confidence=True).
- compute Precision, Recall and Accuracy (optional) with evaluate_performance().
- improve relative imports inside package.
- ... bugfixes.
- functionality for dynamic quantization, fp32 to fp16, padding parametrized.
- remove precooked DA_BERT_ML_16BIT, include precooked DA_DISTILBERT_ML.
- include 16 bit FP precooked DA_BERT_ML_16BIT.
- Support new versions of
transformers
(4.x) andtorch
- BUGFIX: Restrict torch version.
- Do not import datasets as part of Precooked Models.
- Do not load datasets if not provided by user.
- First official release.