| ## Knowledge encoding by examples of Word2Vec and LLM training |
| This repository contains weights for a list of language models: |
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| - 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). |
