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Write With Transformer
Hugging Face released a new version of their Write With Transformer app, using a language model trained directly on Arxiv to generate Deep Learning and NLP completions!
In addition, they add state-of-the-art NLP models such as GPT, GPT-2 and XLNet completions:

https://transformer.huggingface.co/

H / T : Lysandre Debut
#Transformer #Pytorch #NLP

@ArtificialIntelligenceArticles
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets
Geva et al.: https://arxiv.org/abs/1908.07898
#ArtificialIntelligence #MachineLearning #NLP
What Kind of Language Is Hard to Language-Model?
Mielke et al.: https://arxiv.org/abs/1906.04726
#ArtificialIntelligence #MachineLearning #NLP
Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch
By 🤗 Hugging Face : https://huggingface.co/transformers
#Transformers #MachineLearning #NLP
News classification using classic Machine Learning tools (TF-IDF) and modern NLP approach based on transfer learning (ULMFIT) deployed on GCP

By Imad El Hanafi

Live version: https://nlp.imadelhanafi.com/

Github: https://github.com/imadelh/NLP-news-classification

Blog: https://imadelhanafi.com/posts/text_classification_ulmfit/

#DeepLearning #MachineLearning #NLP
Specializing Word Embeddings (for Parsing) by Information Bottleneck
Li et al.: https://www.aclweb.org/anthology/D19-1276.pdf
#ArtificialIntelligence #MachineLearning #NLP
The Illustrated GPT-2 (Visualizing Transformer Language Models)
Blog by Jay Alammar : https://jalammar.github.io/illustrated-gpt2/
#ArtificialIntelligence #NLP #UnsupervisedLearning
A tutorial to implement state-of-the-art NLP models with Fastai for Sentiment Analysis
Maximilien Roberti : https://towardsdatascience.com/fastai-with-transformers-bert-roberta-xlnet-xlm-distilbert-4f41ee18ecb2
#FastAI #NLP #Transformers
Major trends in #NLP : a review of 20 years of #ACL research

The 57th Annual Meeting of the Association for Computational Linguistics (ACL 2019) is starting this week in Florence, Italy. We took the opportunity to review major research trends in the animated NLP space and formulate some implications from the business perspective. The article is backed by a statistical and — guess what — NLP-based analysis of ACL papers from the last 20 years

https://towardsdatascience.com/major-trends-in-nlp-a-review-of-20-years-of-acl-research-56f5520d473
exBERT- A Visual Analysis Tool to Explore Learned Representations in Transformers Models
Benjamin Hoover, Hendrik Strobelt, Sebastian Gehrmann : http://exbert.net
#NLP #BERT #LanguageModel
JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation
Mao et al.: https://arxiv.org/abs/2005.03361
#ArtificialIntelligence #DeepLearning #NLP