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license: mit
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# Moving Average Gated Attention (Mega): Pretrained LM

This repo contains pretrained weights for a language model with the Mega architecture (see [paper](https://arxiv.org/abs/2209.10655)). 
I used the Mega source code (namely the `MegaEncoderLayer` class) and created wrappers for token embeddings and MLM prediction. This model
was pretrained for 5 epochs (11.3k gradient steps) on wikitext-103, which took roughly 5 hours on a single T4 (in Colab's free tier).

See [the Colab notebook](https://colab.research.google.com/drive/1qfUO6o5HRdxBblWlw058HVyvaEPhPpH8?usp=sharing) 
for further training details. In order to load the pretrained weights for this model, you'll need to use the 
[Mega repo](https://github.com/facebookresearch/mega) along with the example code at the end of the Colab notebook.