## 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](https://arxiv.org/abs/1402.3722). 
- 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.

[Training code can be found on GitHub](https://github.com/RuslanPeresy/knowledge-encode).