word2vec Explained: deriving Mikolov et al.'s negative-sampling word-embedding method
Paper • 1402.3722 • Published
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Knowledge encoding by examples of Word2Vec and LLM training
This repository contains weights for a list of language models:
- word2vec.pt: embedding trained on 150mil pairs of text tokens subsampled from text8 dataset. SkipGram method with negative sampling was used as described in the original paper.
- mlp.pt: 2-layers MLP trained on the same dataset and using pretrained embeddings.
- mlp_norm.pt: Version of the MLP model utilizing LayerNorm for better scaling of the learned features distribution.
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