practical-pytorch and practical-torchtext
These two tools are **complementary**: the deprecated `practical-pytorch` repo offered general PyTorch tutorials, while `practical-torchtext` provides specific tutorials for using the `torchtext` library, making the latter useful for NLP practitioners who might have learned general PyTorch concepts from resources like the former (or its modern equivalents) and now want to apply them to text data.
About practical-pytorch
spro/practical-pytorch
Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained
Covers character-level and sequence-to-sequence RNN architectures for NLP tasks including text classification, generation, and machine translation with attention mechanisms. Implements practical applications like name classification, Shakespeare text generation, and neural machine translation using PyTorch's autograd and embedding layers. Jupyter notebooks demonstrate end-to-end workflows with internet-sourced datasets and GloVe word vectors.
About practical-torchtext
keitakurita/practical-torchtext
A set of tutorials for torchtext
These tutorials help you learn how to process text data for common natural language processing tasks. You'll input raw text and learn how to prepare it for machine learning models, leading to outputs like categorized text or predicted next words in a sequence. This is for anyone building or understanding text-based AI, particularly researchers and data scientists working with PyTorch.
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