Skip-Gram Word2Vec model with Hierarchical Softmax in PyTorch
Project description
SkipGram-HS 🧠
A PyTorch implementation of the Skip-Gram model with Hierarchical Softmax from scratch.
Features
- Train skip-gram embeddings on your own corpus or NLTK's Brown corpus.
- Hierarchical softmax for efficient training on large vocabularies.
- Save trained embeddings and training loss history.
- Analogy evaluation (e.g., king - man + woman ≈ queen).
Installation
Install directly from GitHub:
pip install git+https://github.com/agentksimha/skip_gram.git
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