Can a simple deep Transformer model able to learn to be a calculator?
For example:
- input:
"((272-844+960)+257)*711"
, output:"458595"
. - input:
"776/(41*988)/414*991"
, output:"0.045856"
.
This repo is an educational tutorial for writing a simple PyTorch Transformer model with custom dataset.
- conda create -n tfcal_env python=3.10.13
- conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
- pip install jupyterlab jupyterlab-sublime tqdm