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Awesome GitHub RepositoriesBidirectional LSTM Models
Recurrent neural network architectures that process sequences in both forward and backward directions.
Distinct from Linear-Time Sequence Models: None of the sequence-to-sequence candidates specifically cover the bidirectional LSTM architecture for sequence modeling.
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Awesome Bidirectional LSTM Models GitHub Repositories
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- macanv/bert-bilsmt-crf-ner
macanv/BERT-BiLSMT-CRF-NER
4,906عرض على GitHubThis project is a natural language processing system designed for named entity recognition and text classification. It uses a machine learning approach to identify specific names and key information from raw text to organize unstructured content into a structured format. The system implements a multi-layer architecture that combines a pre-trained transformer for embeddings, bidirectional long short-term memory for sequence modeling, and a conditional random field for label transitions. It supports transfer learning through the fine-tuning of these models on task-specific datasets. The projec
Uses bidirectional LSTM layers to capture long-range dependencies within sentences.
Python
