Dlabs.ai

AUGUST 10, 2020

On principle, all chatbots work by utilising some form of natural language processing (NLP). The challenges of intent detection One of the biggest challenges in building successful intent detection is, of course, natural language processing. at the SentiCognitiveServies project ).

Natural Language Processing 52

Natural Language Processing Chatbots Neural Network Machine Learning 52

Lexalytics

APRIL 5, 2021

Going forward, it was clear that we would need to be supporting even more models across more languages, yet our code and training data were scattered across many cloud computing instances. This is the sort of representation that is useful for natural language processing. The base model of BERT [ 103 ] had 12 (!)

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Sebastian Ruder

DECEMBER 6, 2021

Reading Comprehension assumes a gold paragraph is provided Standard approaches for reading comprehension build on pre-trained models such as BERT. Using BERT for reading comprehension involves fine-tuning it to predict a) whether a question is answerable and b) whether each token is the start and end of an answer span.

BERT 52

BERT NLP Natural Language Processing Computational Linguistics 52

Sebastian Ruder

OCTOBER 26, 2019

In particular, I cover unsupervised deep multilingual models such as multilingual BERT. Depending on the task, there are other ways of transferring information across languages such as by domain adaptation (as seen above), annotation projection ( Padó & Lapata, 2009 ; Ni et al., 2016 ; Eger et al., 2016 ; Lample et al.,

BERT 52

BERT NLP Natural Language Processing Neural Network 52

Sebastian Ruder

JANUARY 19, 2021

The selection of areas and methods is heavily influenced by my own interests; the selected topics are biased towards representation and transfer learning and towards natural language processing (NLP). Pre-trained language models were found to be prone to generating toxic language ( Gehman et al., 2020 ; Rust et al.,

NLP 52

NLP ML Computer Vision Natural Language Processing 52

Sebastian Ruder

JANUARY 24, 2022

2021) 2021 saw many exciting advances in machine learning (ML) and natural language processing (NLP). 6] such as W2v-BERT [7] as well as more powerful multilingual models such as XLS-R [8]. Advances in Neural Information Processing Systems, 2020. Credit for the title image: Liu et al. Why is it important?  

NLP 52

NLP ML BERT Computational Linguistics 52

AWS Machine Learning Blog

SEPTEMBER 11, 2024

The benchmark used is the RoBERTa-Base, a popular model used in natural language processing (NLP) applications, that uses the transformer architecture. For the latter instance type, they ran three tests: language pretraining with GPT2, token classification with BERT Large, and image classification with the Vision Transformer.

ML 93

ML Deep Learning Algorithm Large Language Models 93

Unite.AI

SEPTEMBER 20, 2023

Large language models or LLMs are AI systems that use transformers to understand and create human-like text. Hugging Face , started in 2016, aims to make NLP models accessible to everyone. It is based in New York and was founded in 2016." We choose a BERT model fine-tuned on the SQuAD dataset.

LLM 342

LLM BERT NLP Python 342