Gensim vs Transformers: What are the differences?
Gensim: A python library for Topic Modelling. 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; 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.
Gensim and Transformers can be primarily classified as "NLP / Sentiment Analysis" tools.
Gensim is an open source tool with 10.8K GitHub stars and 3.74K GitHub forks. Here's a link to Gensim's open source repository on GitHub.