shibing624/nlp-tutorial
A comprehensive NLP tutorial covering word embeddings, pretrained language models (BERT, GPT, ELECTRA), text classification, translation, and dialogue systems with PyTorch implementations.
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This repository provides a collection of Jupyter Notebook tutorials for natural language processing tasks. It includes implementations of word embeddings, lexical analysis with LSTM and CRF, pretrained language models such as BERT, ELECTRA, ELMO, and GPT, as well as examples for text classification, semantic matching, machine translation, and dialogue systems. The tutorials serve as learning materials for beginners entering NLP and PyTorch development.
Frequently asked
- What is shibing624/nlp-tutorial?
- A comprehensive NLP tutorial covering word embeddings, pretrained language models (BERT, GPT, ELECTRA), text classification, translation, and dialogue systems with PyTorch implementations.
- Is nlp-tutorial open source?
- Yes — shibing624/nlp-tutorial is open source, released under the Apache-2.0 license.
- What language is nlp-tutorial written in?
- shibing624/nlp-tutorial is primarily written in Jupyter Notebook.
- How popular is nlp-tutorial?
- shibing624/nlp-tutorial has 487 stars on GitHub.
- Where can I find nlp-tutorial?
- shibing624/nlp-tutorial is on GitHub at https://github.com/shibing624/nlp-tutorial.