GPyT is a GPT2 model trained from scratch (not fine tuned) on Python code from Github. Overall, it was ~80GB of pure Python code, the current GPyT model is a mere 2 epochs through this data, so it may benefit greatly from continued training and/or fine-tuning.
Newlines are replaced by <N>
Input to the model is code, up to the context length of 1024, with newlines replaced by <N>
Here's a quick example of using this model:
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("Sentdex/GPyT")
model = AutoModelWithLMHead.from_pretrained("Sentdex/GPyT")
# copy and paste some code in here
inp = """import"""
newlinechar = "<N>"
converted = inp.replace("\n", newlinechar)
tokenized = tokenizer.encode(converted, return_tensors='pt')
resp = model.generate(tokenized)
decoded = tokenizer.decode(resp[0])
reformatted = decoded.replace("<N>","\n")
print(reformatted)
Should produce:
import numpy as np
import pytest
import pandas as pd<N
This model does a ton more than just imports, however. For a bunch of examples and a better understanding of the model's capabilities: https://pythonprogramming.net/GPT-python-code-transformer-model-GPyT/
Considerations:
- This model is intended for educational and research use only. Do not trust model outputs.
- Model is highly likely to regurgitate code almost exactly as it saw it. It's up to you to determine licensing if you intend to actually use the generated code.
- All Python code was blindly pulled from github. This means included code is both Python 2 and 3, among other more subtle differences, such as tabs being 2 spaces in some cases and 4 in others...and more non-homologous things.
- Along with the above, this means the code generated could wind up doing or suggesting just about anything. Run the generated code at own risk...it could be anything