HelenaHlz's Stars
huggingface/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
bert-nmt/bert-nmt
google-research/electra
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
delip/PyTorchNLPBook
Code and data accompanying Natural Language Processing with PyTorch published by O'Reilly Media https://amzn.to/3JUgR2L
prakashpandey9/Text-Classification-Pytorch
Text classification using deep learning models in Pytorch
tomohideshibata/BERT-related-papers
BERT-related papers
kanyun-inc/fairseq-gec
Source code for paper: Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data
jayavardhanr/End-to-end-Sequence-Labeling-via-Bi-directional-LSTM-CNNs-CRF-Tutorial
Tutorial for End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
grammatical/neural-naacl2018
Neural models and instructions on how to reproduce our results for our neural grammatical error correction systems from M. Junczys-Dowmunt, R. Grundkiewicz, S. Guha, K. Heafield: Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task, NAACL 2018.
grammatical/pretraining-bea2019
Models, system configurations and outputs of our winning GEC systems in the BEA 2019 shared task described in R. Grundkiewicz, M. Junczys-Dowmunt, K. Heafield: Neural Grammatical Error Correction Systems with Unsupervised Pre-training on Synthetic Data, BEA 2019.
nusnlp/mlconvgec2018
Code and model files for the paper: "A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction" (AAAI-18).
ZeroWangZY/federated-learning
Everything about Federated Learning (papers, tutorials, etc.) -- 联邦学习
sebastianruder/NLP-progress
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
stanfordnlp/CoreNLP
CoreNLP: A Java suite of core NLP tools for tokenization, sentence segmentation, NER, parsing, coreference, sentiment analysis, etc.
jaehyunp/stanfordacm
Stanford ACM-ICPC related materials
fengdu78/lihang-code
《统计学习方法》的代码实现