CHANGES.txt

2019
v0.8.0 Mon Aug 19th
  - BERT low memory mode
  - RoBERTa base model support
v0.7.1 Thu June 27th
  - Fix for cached_predict() on long sequences
v0.7.0 Thu June 27th
  - GPT2-medium support
  - Support for adapter finetuning strategy
  - Add DeploymentModel class
v0.6.7 Thu May 30th
  - Refactor sequence labeling functions
  - Fix learning rate / tqdm issue for long documents
v0.6.5 Thu May 23rd
  - Fix subtoken_predictions flag
  - Only download required subset of model files lazily
v0.6.4 Tue May 14th
  - Add BERT support
v0.6.3 Thu May 2nd
  - Option to control maximum percentage of memory used
  - Attention weight visualization for GPT
  - Assorted bug fixes
v0.6.2 Thu Apr 4th
  - Cached predict fix
  - Model download fix
v0.6.1 Fri Mar 29th
  - MTL bug fix
  - Validation / early-stopping bug fix
v0.6.0 Thu Mar 28th
  - Support for new base models
  - GPT2 support
  - Multi-task learning support
  - Word CNN Baseline
  - Code base refactor


2018
v0.5.9 Wed Oct 24th -- Resolve issues with running multiple concurrent finetune models
v0.5.1 Thu Oct 19th -- Fix lazy encoder install
v0.5.0 Tue Oct 17th -- Move core finetune infrastructure to tf.Estimator API for major model speedup!