graykode/nlp-tutorial
Natural Language Processing Tutorial for Deep Learning Researchers
We leverage 14 datasets as OOD test data and conduct evaluations on 8 NLU tasks over 21 popularly used models. Our findings confirm that the OOD accuracy in NLP tasks needs to be paid more attention to since the significant performance decay compared to ID accuracy has been found in all settings.
$ git clone https://github.com/YangLinyi/GLUE-X.gitNatural Language Processing Tutorial for Deep Learning Researchers
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💥 Fast State-of-the-Art Tokenizers optimized for Research and Production
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BertViz: Visualize Attention in Transformer Models
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
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State of the Art Natural Language Processing
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A Unified Library for Parameter-Efficient and Modular Transfer Learning
Data from GitHub · snapshot Nov 13, 2026