learning pytorch step by step
the repo contains the following parts:
- pytorch tensor learning
- pytorch linear regression
- CV pretrained model usage
- MLP Model for binary classification
- MLP Model for multi classification
- CNN model for MNIST
- CNN model for digital captcha recognition
- CNN model for variable length math operation captcha recognition
- Bi-LSTM CRF Model for Chinese Named Entity Recognize
- HuggingFace Transformers NLP tasks learning
- language model
- multiclass text classification
- English named entity recognition
- Chinese named entity recognition
- onnx model serving:
- official SSD model
- IRIS dataset MLP multiclass classification Model
- captcha recognition CNN Model
- transformers BERT text classification Model
- HuggingFace Learning, include Datasets, Trainer, BERT dynamic quantization
- PyTorch Tutorial: How to Develop Deep Learning Models with Python: https://machinelearningmastery.com/pytorch-tutorial-develop-deep-learning-models/
- Named Entity Recognition (NER) using BiLSTM CRF: https://github.com/Gxzzz/BiLSTM-CRF
- transformers 示例教程: http://pytorchchina.com/2020/03/04/transformers-示例教程/
- 手把手教你用Pytorch-Transformers——实战（二）: https://www.cnblogs.com/dogecheng/p/11911909.html
- transformers_ner: https://colab.research.google.com/github/abhimishra91/transformers-tutorials/blob/master/transformers_ner.ipynb
- Datasets: https://www.huaxiaozhuan.com/%E5%B7%A5%E5%85%B7/huggingface_transformer/chapters/2_datasets.html
- Huggingface详细入门介绍之dataset库：https://zhuanlan.zhihu.com/p/554678463
- Stream: https://huggingface.co/docs/datasets/stream
- HuggingFace教程 Datasets基本操作: Process: https://zhuanlan.zhihu.com/p/557032513
- Introduction to Quantization on PyTorch
- DYNAMIC QUANTIZATION ON BERT
- RFC-0019-Extending-PyTorch-Quantization-to-Custom-Backends