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albert-chinese-ner

使用预训练语言模型ALBERT做中文NER

albert_pytorch

A Lite Bert For Self-Supervised Learning Language Representations

albert_zh

A LITE BERT FOR SELF-SUPERVISED LEARNING OF LANGUAGE REPRESENTATIONS, 海量中文预训练ALBERT模型

attention-visualization

awesome-nlp

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

bdci2019-sentiment-classification

CCF BDCI 2019 互联网新闻情感分析 复赛top1解决方案

bert-for-webqa

用BERT在百度WebQA中文问答数据集上做阅读问答

bert_crf-for-event-extraction

In first step , use BERT+CRF for trigger word recognition. then use recognized trigger word type and relative position for auxiliary information

bert_distill

BERT distillation（基于BERT的蒸馏实验 ）

chatgpt-on-wechat

chinese-text-classification-pytorch

中文文本分类，TextCNN，TextRNN，FastText，TextRCNN，BiLSTM_Attention，DPCNN，Transformer，基于pytorch，开箱即用。

chinese-word-vectors

100+ Chinese Word Vectors 上百种预训练中文词向量

chinese_gpt

100G中文清洗后语料训练的gpt模型

chinese_text_cnn

TextCNN Pytorch实现 中文文本分类 情感分析

clle

Code and Datasets of " CLLE: A Benchmark for Continual Language Learning Evaluation in Multilingual Machine Translation"

clue

中文语言理解基准测评 Chinese Language Understanding Evaluation Benchmark: datasets, baselines, pre-trained models, corpus and leaderboard

cppo

ICLR 2024 CPPO: Continual Learning for Reinforcement Learning with Human Feedback

deepctr

Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

deepfm_with_pytorch

A PyTorch implementation of DeepFM for CTR prediction problem.

dnn_ctr

The framework to deal with ctr problem。The project contains FNN,PNN,DEEPFM, NFM etc

dpo_based_on_trlx

Reproducing the code of "Direct Preference Optimization: Your Language Model is Secretly a Reward Model"

electra_crf_ner

We start a company-name recognition task with a small scale and low quality training data, then using skills to enhanced model training speed and predicting performance with least artificial participation. The methods we use involve lite pre-training models such as Albert-small or Electra-small with financial corpus, knowledge of distillation and multi-stage learning. The result is that we improve the recall rate of company names recognition task from 0.73 to 0.92 and get 4 times as fast as BERT-Bilstm-CRF model.

event-kg-for-ace2005-

使用ACE2005创建以事件和实体为节点的事件知识图谱，用于智能问答

flamingo-pytorch

Implementation of 🦩 Flamingo, state-of-the-art few-shot visual question answering attention net out of Deepmind, in Pytorch

foolnltk

A Chinese Nature Language Toolkit

football

Check out the new game server:

forecasting

Time Series Forecasting Best Practices & Examples

fundamentals-of-deep-learning-book

Code companion to the O'Reilly "Fundamentals of Deep Learning" book

hointpoint_detection

海量文本发现热点话题