This is an accompanying repository to my paper:

• instructions to download the pre-trained language model.
• jupyter notebook to show you how to use the pre-trained model on a text classification task using fastai v2. [notebook]

• Release a pre-trained AWD LSTM language model in Filipino using fastai v2.
• Benchmark AWD LSTM to the Hate Speech Dataset. [reference]

• fastai v2 and up
• NVIDIA GPU (all experiments were done on Colab w/ Tesla T4)

# Install gdown
pip install gdown

# Make directory
mkdir models

# Download data
gdown --id 19jdv8-XEbDNiqlm_lPb1csbVZYkn3gfA

# Unzip
unzip pretrained.zip -d models

# Finally
You should see two files inside 'models' directory: 
1. finetuned_weights_20.pth (pre-trained weights)
2. vocab.pkl (vocab) 

This will be used later in language model fine-tuning. 
See accompanying jupyter notebook to see usage.

Big thanks to Blaise Cruz for answering my questions and for nudging me in the right direction.