--- arxiv: 2103.06333 license: mit language: - code --- This is an *unofficial* reupload of [uclanlp/plbart-base](https://huggingface.co/uclanlp/plbart-base) in the `SafeTensors` format using `transformers` `4.40.1`. The goal of this reupload is to prevent older models that are still relevant baselines from becoming stale as a result of changes in HuggingFace. Additionally, I may include minor corrections, such as model max length configuration. Please see the [original repo](https://github.com/wasiahmad/PLBART) for more information. Original model card below: --- ## PLBART is a Transformer model - PLBART is a sequence-to-sequence model pre-trained on a large collection Java and Python functions and natural language descriptions collected from Github and StackOverflow, respectively. - PLBART is pre-trained via denoising autoencoding (DAE) and uses three noising strategies: token masking, token deletion, and token infilling (shown below in the three examples).
Noisy Input | Original Sequence |
---|---|
Is 0 the [MASK] Fibonacci [MASK] ? <En> | <En> Is 0 the first Fibonacci number ? |
public static main ( String args [ ] ) { date = Date ( ) ; System . out . ( String . format ( " Current Date : % tc " , ) ) ; } <java> | <java> public static void main ( String args [ ] ) { Date date = new Date ( ) ; System . out . printf ( String . format ( " Current Date : % tc " , date ) ) ; } |
def addThreeNumbers ( x , y , z ) : NEW_LINE INDENT return [MASK] <python> | <python> def addThreeNumbers ( x , y , z ) : NEW_LINE INDENT return x + y + z |