language-models

Visualize and explore NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2).

PhoBERT: Pre-trained language models for Vietnamese (EMNLP-2020 Findings)

An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.

ACL'2021: LM-BFF: Better Few-shot Fine-tuning of Language Models

This repository contains landmark research papers in Natural Language Processing that came out in this century.

A package built on top of Hugging Face's transformers library that makes it easy to utilize state-of-the-art NLP models

🤗 ParsBERT: Transformer-based Model for Persian Language Understanding

Pre-trained models and language resources for Natural Language Processing in Polish

This is a list of open-source projects at Microsoft Research NLP Group

Language models are open knowledge graphs ( non official implementation )

Generate realistic Instagram captions using transformers 🤗

A collection of resources on using BERT (https://arxiv.org/abs/1810.04805 ) and related Language Models in production environments.

Must-read papers on Natural Language Processing (NLP)

[ICLR 2021] "InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective" by Boxin Wang, Shuohang Wang, Yu Cheng, Zhe Gan, Ruoxi Jia, Bo Li, Jingjing Liu

UBC ARBERT and MARBERT Deep Bidirectional Transformers for Arabic

Keras implementations of three language models: character-level RNN, word-level RNN and Sentence VAE (Bowman, Vilnis et al 2016).

Smart Language Model

Transformer based Turkish language models

Neural Network Language Model that generates text based off Lord of the Rings. Built with Pytorch.

Python source code for EMNLP 2020 paper "Reusing a Pretrained Language Model on Languages with Limited Corpora for Unsupervised NMT".

The course notes about Stanford CS224n Natural Language Processing with Deep Learning Winter 2019 (using PyTorch)

Deep-learning Transfer Learning models of NTUA-SLP team submitted at the IEST of WASSA 2018 at EMNLP 2018.

Python implementation of an N-gram language model with Laplace smoothing and sentence generation.

Course on Language Technologies and NLP

The data and code for NumerSense (EMNLP2020)

Code for equipping pretrained language models (BART, GPT-2, XLNet) with commonsense knowledge for generating implicit knowledge statements between two sentences, by (i) finetuning the models on corpora enriched with implicit information; and by (ii) constraining models with key concepts and commonsense knowledge paths connecting them.

🦜 NLP for Tibetan, in Python.