Best summary of Natural Language Processing and terms - model (a language model - e.g. BertModel, defines encoder and decoder and their properties), transformer (a specific neural network based on attention paper), encoder (series of transformers on input), decoders (series of transformers on output). Bert does NOT use decoder. TensorFlow and PyTorch are possible backends to Transformers (NN). Summary: BERT is a highly complex and advanced language model that helps people automate language understanding.

Simpliest start with ai. Use the Github code linked in

Use the Bert model to train on Yelp dataset

BigCode is an open scientific collaboration working on the responsible development and use of large language models for code

Hi level only talk about training for a language

My Account and profile on Huggingface - the home of AI transformers, models, training sets

Describes how to train a new language (desperanto) model.

Buy his book from 2008

The secret, he found, was to stick the particle in a “disordered” quantum landscape, one dotted with peaks and valleys. Each location would have a random height, representing a random energy. In a real material, this disorder might come from impurities such as missing atoms or atoms of different elements.

Sometimes a 'read-only' text property is stuck, and we cannot edit a file. This is the reason.

Thread Reader on any Twitter account that publishes it. Does NOT neew Twitter login.

International news in German and all languages.

Turorial and documentation on everything PWA.

Discussion on how to use back button for both browser and PWA

Linked by Tim Bray.

World Atlas of Language Structures (WALS) is a large database of structural (phonological, grammatical, lexical) properties of languages gathered from descriptive materials (such as reference grammars)