What is Transformers?
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.
Transformers is a tool in the Text & Language Models category of a tech stack.
Key Features
High performance on NLU and NLG tasksLow barrier to entry for educators and practitionersDeep learning researchersHands-on practitionersAI/ML/NLP teachers and educators
Transformers Pros & Cons
Pros of Transformers
No pros listed yet.
Cons of Transformers
No cons listed yet.
Transformers Alternatives & Comparisons
What are some alternatives to Transformers?
SpaCy
It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.
rasa NLU
rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.
Gensim
It is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community.
