A lightweight implementation of the Word2Vec algorithm for word embeddings.
smolWord2Vec is a simplified implementation of the Word2Vec model, designed to help users understand the core concepts of word embeddings. This project provides a clean, educational implementation that demonstrates how words can be represented as vectors in a continuous vector space.
- Implementation of the Skip-gram architecture
- Context-based word prediction
- Vector representations of words that capture semantic relationships