readme: ---
  license: mit
  datasets:
  - wikitext
  language:
  - en
  pipeline_tag: fill-mask
  ---
  
  # 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.