NLP

EleutherAI web app testing for language models — Lees op 6b.eleuther.ai/

State of the Art Natural Language Processing. Contribute to JohnSnowLabs/spark-nlp development by creating an account on GitHub. — Lees op github.com/JohnSnowLabs/spark-nlp/releases/tag/3.1.0

The sentiment is an attitude or opinion that is expressed, it is not based on laws and philosophy. Sentiment analysis is the mining of opinion or sentiment expressed in text as positive, negative or neutral sentiment. Detecting sarcasm is the main hurdle in sentiment analysis. Sarcasm can be expressed in Read more

Top NLP Code Repositories – Quantum Stat — Lees op index.quantumstat.com/

Provides two examples of topic classification, categorizing a text document into one of a predefined set of topics. — Lees op developers.google.com/machine-learning/guides/text-classification

SentenceTransformers is a Python framework for state-of-the-art sentence, text and image embeddings. The initial work is described in our paper Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. You can use this framework to compute sentence / text embeddings for more than 100 languages. These embeddings can then be compared e.g. with Read more

The Super Duper NLP Repo — Lees op notebooks.quantumstat.com/

The first version of FastAPI has been released by the end of 2018 and it’s been increasingly used in many applications in production since then. That’s what we are using behind the hood at NLP Cloud. It is a great way to easily and efficiently serve our hundreds of NLP Read more

Multiple studies have shown that BERT is remarkably robust to pruning, yet few if any of its components retain high importance across downstream tasks. Contrary to this received wisdom, we demonstrate that pre-trained Transformer encoders are surprisingly fragile to the removal of a very small number of scaling factors and Read more

We show that Transformer encoder architectures can be massively sped up, with limited accuracy costs, by replacing the self-attention sublayers with simple linear transformations that “mix” input tokens. These linear transformations, along with simple nonlinearities in feed-forward layers, are sufficient to model semantic relationships in several text classification tasks. Perhaps Read more