SeanLee97 / simnet
基于numpy实现的简单神经网络框架
☆15Updated 6 years ago
Related projects ⓘ
Alternatives and complementary repositories for simnet
- Natural Language Procesing☆34Updated 3 years ago
- bert-of-theseus via bert4keras☆31Updated 4 years ago
- Python下shuffle几百G文件☆33Updated 3 years ago
- AI Challenger 2018 阅读理解赛道代码分享☆20Updated 5 years ago
- Keras implement of Lazy optimizer☆21Updated 4 years ago
- a beautiful method for cluster or community detection☆49Updated 5 years ago
- saving memory by recomputing for keras☆37Updated 4 years ago
- This is our solution for KDD Cup 2020. We implemented a very neat and simple neural ranking model based on siamese BERT which ranked firs…☆70Updated 4 years ago
- adafactor optimizer for keras☆20Updated 3 years ago
- A simple middleware to improving GPU utilization then speedup online inference.☆19Updated 3 years ago
- LGEB: Benchmark of Language Generation Evaluation☆16Updated 2 years ago
- Adversarial Training for NLP in Keras☆46Updated 4 years ago
- 无监督文本生成的一些方法☆49Updated 3 years ago
- 高性能小模型测评 Shared Tasks in NLPCC 2020. Task 1 - Light Pre-Training Chinese Language Model for NLP Task☆57Updated 4 years ago
- lightweighted deep learning inference service framework☆38Updated 3 years ago
- multi-task classifier☆21Updated last year
- machine reading comprehension with deep learning☆20Updated 6 years ago
- top8 KDD Cup 2020 Challenges for Modern E-Commerce Platform: Multimodalities Recall☆36Updated 2 years ago
- 2019中国高校计算机大赛——大数据挑战赛 第一名解决方案☆41Updated 4 years ago
- 基于BERT的预训练语言模型实现,分为两步:预训练和微调。目前已包括BERT、Roberta、ALbert三个模型,且皆可支持Whole Word Mask模式。☆16Updated 4 years ago
- bert4keras实现gpt下中国象棋☆43Updated 4 years ago
- NLP Project + pytorch☆10Updated 4 years ago
- CLUE Emotion Analysis Dataset 细粒度情感分析数据集☆8Updated 4 years ago
- 分享一些S2S在实际应用中遇到的问题和解决方法。☆27Updated 4 years ago
- Official code of our work, Robust, Transferable Sentence Representations for Text Classification [Arxiv 2018].☆20Updated 6 years ago
- pytorch版bert权重转tf☆21Updated 4 years ago
- 基于Transformer的单模型、多尺度的VAE模型☆53Updated 3 years ago