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Wikipedia2Vec is an embedding learning tool that creates word and entity vector representations from Wikipedia, enabling NLP models to leverage structured and contextual knowledge.
Features
- Generates word and entity embeddings from Wikipedia corpus
- Open-source and designed for NLP research and knowledge-based tasks
- Supports joint learning of word and entity representations
- Works with both structured (infoboxes) and unstructured text
- Provides pretrained models for various languages
- Compatible with deep learning frameworks like PyTorch and TensorFlow
Project Samples
Categories
Natural Language Processing (NLP)License
Apache License V2.0Follow Wikipedia2Vec
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