Wit vs Transformers: What are the differences?

Wit: Natural Language for the Internet of Things. Turn speech into actionable data. Wit enables developers to add a modern natural language interface to their app or device with minimal effort. Precisely, Wit turns sentences into structured information that the app can use. Developers don’t need to worry about Natural Language Processing algorithms, configuration data, performance and tuning. Wit encapsulates all this and lets you focus on the core features of your apps and devices; Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0. It provides general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet…) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between TensorFlow 2.0 and PyTorch.

Wit and Transformers can be primarily classified as "NLP / Sentiment Analysis" tools.

Some of the features offered by Wit are:

• Voice-enabled Android and iOS apps
• Rasberry Pi based home automation commanded by speech
• Google Glass apps accepting voice commands

On the other hand, Transformers provides the following key features:

• High performance on NLU and NLG tasks
• Low barrier to entry for educators and practitioners
• Deep learning researchers