Details

This is a roBERTa-base model trained on the python part of CodeSearchNet and reached a dev perplexity of 3.296

This model was used for the Programming Puzzles enumerative solver baseline detailed in Programming Puzzles paper.

Usage

You can either load the model and further fine-tune it for a target task (as done for the puzzle solver), or you can experiment with mask-filling directly with this model as in the following example:

from transformers import AutoTokenizer, AutoModelWithLMHead, pipeline

tokenizer = AutoTokenizer.from_pretrained("tals/roberta_python")

code = """sum= 0
sum += i
assert sum == 6
"""
demo(code)


BibTeX entry and citation info

@inproceedings{
schuster2021programming,
title={Programming Puzzles},
author={Tal Schuster and Ashwin Kalyan and Alex Polozov and Adam Tauman Kalai},
booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 1)},
year={2021},
url={https://openreview.net/forum?id=fe_hCc4RBrg}
}

Mask token: <mask>