3 ms·
Show HN: Autocomplete Python Code with Transformers
This is a small project we created to train a character level autoregressive transformer (or LSTM) model to predict Python source code. We trained it on GitHub repositories found on awesome pytorch list.
Github repo: https://github.com/lab-ml/python_autocomplete
You can try training on Google Colab: https://colab.research.google.com/github/lab-ml/python_autocomplete/blob/master/notebooks/train.ipynb
Here are some sample evaluations/visualizations of the trained model: https://colab.research.google.com/github/lab-ml/python_autocomplete/blob/master/notebooks/evaluate.ipynb
Working on a simple VSCode extension to test this out. Will open source it soon on the same repository.
- vpj 6y agoLinks: Github repo: https://github.com/lab-ml/python_autocomplete https://github.com/lab-ml/python_autocomplete Training notebook: https://colab.research.google.com/github/lab-ml/python_autocomplete/blob/master/notebooks/train.ipynb https://colab.research.google.com/github/lab-ml/python_autoc... Evaluation notebook: https://colab.research.google.com/github/lab-ml/python_autocomplete/blob/master/notebooks/evaluate.ipynb https://colab.research.google.com/github/lab-ml/python_autoc...
- alexanderrofail 6y agohttps://www.kite.com/ https://www.kite.com/ does this too, claiming 47% less keystrokes. They are a good benchmark to set for seeing how efficient the model can get.