Sentence Transformers
What is Sentence Transformers?
It provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various tasks.
Sentence Transformers is a tool in the Text & Language Models category of a tech stack.
Key Features
Vector representations for sentences, paragraphs, and imagesBased on transformer networks like BERT / RoBERTa / XLM-RoBERTa
Sentence Transformers Pros & Cons
Pros of Sentence Transformers
No pros listed yet.
Cons of Sentence Transformers
No cons listed yet.
Sentence Transformers Alternatives & Comparisons
What are some alternatives to Sentence Transformers?
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.
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.
