Let me explain: my custom data are domain specific (ie: aerospace domain) therefore, there is a good chance that many of my worlds was not in the initial training corpus use … A good sentence encoder will encode the three sentences in such a way that the vectors for 1 and 2 are closer to each other than say 1 and 3.

TensorFlow.js is a framework built by Google which enables machine learning in JavaScript. Universal Sentence Encoder is a transformer-based NLP model widely used for embedding sentences or words. The Universal Sentence Encoder encodes text into high dimensional vectors that can be used for text classification, semantic similarity, clustering, and other natural language tasks.

doc_2 = nlp … The models are efficient and result in accurate performance on diverse transfer tasks. This is where the “Universal Sentence Encoder” comes into the picture. universal-sentence-encoder/1 The models take as input English strings and produce as output a fixed dimensional embedding representation of the string. Posted by Yinfei Yang and Amin Ahmad, Software Engineers, Google Research Since it was introduced last year, “Universal Sentence Encoder (USE) for English’’ has become one of the most downloaded pre-trained text modules in Tensorflow Hub, providing versatile sentence embedding models that convert sentences into vector representations.These vectors capture rich semantic information … In the past

Hello all, I have the same concern than @choran..

Universal sentence encoder is a language model that encodes text into fixed-length embeddings. We present models for encoding sentences into embedding vectors that specifically target transfer learning to other NLP tasks. The Universal Sentence Encoder encodes text into high dimensional vectors that can be used for text classification, semantic similarity, clustering, and other natural language tasks.

Deep Averaging network in Universal sentence encoder. A tutorial for embedding Google's USE into your Keras models. Universal Sentence Encoder Visually Explained 6 minute read With transformer models such as BERT and friends taking the NLP research community by storm, it might be tempting to just throw the latest and greatest model at a problem and declare it done. TensorFlow.js; Universal sentence encoder; Angular; TensorFlow.js. It aims to convert sentences into semantically-meaningful fixed-length vectors.. With the vectors produced by the universal sentence encoder, we can use it for various natural language processing tasks, such as classification and textual similarity analysis..