Lexalytics

APRIL 5, 2021

This is the sort of representation that is useful for natural language processing. ELMo would also be the first of the Muppet-themed language models that would come to include ERNIE [ 120 ], Grover [ 121 ]….and The base model of BERT [ 103 ] had 12 (!) layers of bidirectional Transformers.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Explosion

MAY 17, 2023

A lot of people are building truly new things with Large Language Models (LLMs), like wild interactive fiction experiences that weren’t possible before. But if you’re working on the same sort of Natural Language Processing (NLP) problems that businesses have been trying to solve for a long time, what’s the best way to use them?

LLM 135

LLM NLP Large Language Models OpenAI 135

Sebastian Ruder

NOVEMBER 14, 2022

Models that allow interaction via natural language have become ubiquitious. Research models such as BERT and T5 have become much more accessible while the latest generation of language and multi-modal models are demonstrating increasingly powerful capabilities. Transfer learning in natural language processing.

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics BERT 52

Sebastian Ruder

FEBRUARY 24, 2021

Fine-tuning a pre-trained language model (LM) has become the de facto standard for doing transfer learning in natural language processing. 2018 ) while pre-trained language models are favoured over models trained on translation ( McCann et al., 2018 ), natural language inference ( Conneau et al.,

Natural Language Processing 52

Natural Language Processing BERT NLP Computer Vision 52

John Snow Labs

MAY 18, 2023

Word embeddings are considered as a type of representation used in natural language processing (NLP) to capture the meaning of words in a numerical form. Word embeddings are used in natural language processing (NLP) as a technique to represent words in a numerical format. setInputCol('text').setOutputCol('document')

NLP 52

NLP Machine Learning Python Algorithm 52

ODSC - Open Data Science

JANUARY 29, 2024

GANs, introduced in 2014 paved the way for GenAI with models like Pix2pix and DiscoGAN. Data Analysis Data analysis is often overlooked, but it’s still an essential skill for interpreting results from AI models and for the iterative process of improving prompt responses.

Prompt Engineer 52

Prompt Engineer Prompt Engineering Data Science LLM 52

Marek Rei

NOVEMBER 12, 2019

Below you will find short summaries of a number of different research papers published in the areas of Machine Learning and Natural Language Processing in the past couple of years (2017-2019). link] A bidirectional transformer architecture for pre-training language representations. NAACL 2019.

Machine Learning 52

Machine Learning NLP Neural Network BERT 52

Bugra Akyildiz

AUGUST 10, 2024

Large models like GPT-3 (175B parameters) or BERT-Large (340M parameters) can be reduced by 75% or more. Running BERT models on smartphones for on-device natural language processing requires much less energy due to resource constrained in smartphones than server deployments.

BERT 59

BERT Large Language Models Categorization Deep Learning 59

NLP People

JULY 24, 2019

Especially pre-trained word embeddings such as Word2Vec, FastText and BERT allow NLP developers to jump to the next level. On the other hand, a new and pretty disruptive mechanism for sequential processing – attention – has been introduced in the sequence-to-sequence (seq2seq) model by Sutskever et al. White (2014). Hazarika, S.

NLP 52

NLP Neural Network Deep Learning Natural Language Processing 52