graykode/nlp-tutorial Alternatives

Choose when you need a broader PyTorch tutorial that also covers NLP, rather than only NLP models.

PyTorch Tutorial for Deep Learning Researchers

Choose when you want to learn to use the HuggingFace Transformers library instead of implementing models from scratch.

Transformers 库快速入门教程

Choose for a comprehensive university-style deep learning course (Chinese) that includes NLP among many topics.

《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

Choose for a full NLP course with lectures and assignments; more structured than the seed's code snippets.

YSDA course in Natural Language Processing

Choose for a broad collection of NLP documents and code; less code-centric than the seed.

Documents, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation)，etc.

Choose for an in-depth, focused tutorial on sentiment analysis with PyTorch.

Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

Choose for an older but classic NLP-in-PyTorch notebook tutorial; it is no longer maintained.

An IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.

Choose for a textbook-based approach with code from the O'Reilly NLP with PyTorch book.

Code and data accompanying Natural Language Processing with PyTorch published by O'Reilly Media https://amzn.to/3JUgR2L

Deprecated and archived; only useful for historical reference.

Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained

Choose for a focused seq2seq tutorial; deeper on encoder-decoder but narrower than the seed.

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

Older PyTorch version of Dive into Deep Learning; comprehensive textbook but broader than the seed.

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。

Choose for an older TensorFlow NLP model collection; only if you need TensorFlow.

Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0

Choose for a single-model deep dive into building a GPT/LLM from scratch; narrower but very detailed.

Build a modern LLM from scratch. Every line commented. Explained like we are five.