基于 bert4keras 的一个baseline 不作任何 数据trick 单模 线上 最高可到 0.7891 # 基础 版 train.py 0.7769 # transformer 各层 cls concat 明神的trick https://xv44586.github.io/2021/01/20/ccf-qa-2/ train_concat.py 0.7786 # 使用那个FGM对抗 train_FGM.py 0.7891 # 苏神提出的 PET train_PET.py 0.7812 预训练模型使用 nezha 使用说明： 数据放在 data下 下载预训练模型解压 模型会保存在 train中 优化方向： 1，融合🙃 bert4keras >= 0.10.0 nezha的预训练模型 链接: https://pan.baidu.com/s/1lURyXs39PYnsb4imCjVkfQ 密码: 1eqq --来自百度网盘超级会员V4的分享
“英特尔创新大师杯”深度学习挑战赛 赛道3：CCKS2021中文NLP地址相关性任务
Overview
Code release for Universal Domain Adaptation(CVPR 2019)
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Contrastive Multi-View Representation Learning on Graphs
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working repo for my xumx-sliCQ submissions to the ISMIR 2021 MDX
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PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
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Filtering variational quantum algorithms for combinatorial optimization
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A minimal solution to hand motion capture from a single color camera at over 100fps. Easy to use, plug to run.
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A minimal yet resourceful implementation of diffusion models (along with pretrained models + synthetic images for nine datasets)
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This repository provides an efficient PyTorch-based library for training deep models.
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