SPUContext Models

• SentencePiece Unigram Context (SPUContext) models are added for Named Entity Recognition, Dependency Parsing, Part of Speech Tagging and Sentiment Analysis. These are the default models now.
• SPUContext models are even more compact, up to 4x faster and perform significantly better. See metrics table on the main page for comparison.
• SPUContext models use SentencePiece Unigram tokenization.
• Wheel file is 80% smaller now, and each model downloads its weights when it is initialized for the first time.
• In order to evaluate a DL based model, use "evaluate = True" flag while initializing, e.g., NamedEntityRecognizer(model = 'CharNER', evaluate = True). This will load the weights that are NOT trained with test sets.
• Former Python API has become a generic user API, creating an abstraction for the implemented methods. Desired model can be initialized using the "model" argument, e.g., NamedEntityRecognizer(model = 'CharNER').