textClassifier and a-PyTorch-Tutorial-to-Text-Classification

These are ecosystem siblings—both are independent educational implementations of the same hierarchical attention network architecture for document classification, with the first being a ready-to-use classifier and the second being a tutorial-oriented codebase for learning the approach.

Maintenance 0/25
Adoption 10/25
Maturity 9/25
Community 25/25
Maintenance 0/25
Adoption 10/25
Maturity 9/25
Community 22/25
Stars: 1,080
Forks: 374
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
Stars: 249
Forks: 54
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About textClassifier

richliao/textClassifier

Text classifier for Hierarchical Attention Networks for Document Classification

Implements three distinct architectures—hierarchical attention networks with word and sentence-level attention, CNNs with convolutional filters, and bidirectional LSTMs with attention mechanisms—all built on Keras. Supports interpretability by extracting attention weights to identify important words for predictions. Compatible with pre-trained GloVe embeddings and includes training pipelines on standard datasets like IMDB reviews.

About a-PyTorch-Tutorial-to-Text-Classification

sgrvinod/a-PyTorch-Tutorial-to-Text-Classification

Hierarchical Attention Networks | a PyTorch Tutorial to Text Classification

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