---
library_name: transformers.js
base_model:
- neulab/codebert-javascript
pipeline_tag: fill-mask
---



# codebert-javascript (ONNX)


This is an ONNX version of [neulab/codebert-javascript](https://huggingface.co/neulab/codebert-javascript). It was automatically converted and uploaded using [this Hugging Face Space](https://huggingface.co/spaces/onnx-community/convert-to-onnx).


## Usage with Transformers.js


See the pipeline documentation for `fill-mask`: https://huggingface.co/docs/transformers.js/api/pipelines#module_pipelines.FillMaskPipeline


---


This is a `microsoft/codebert-base-mlm` model, trained for 1,000,000 steps (with `batch_size=32`)  on **JavaScript** code from the `codeparrot/github-code-clean` dataset, on the masked-language-modeling task.

It is intended to be used in CodeBERTScore: [https://github.com/neulab/code-bert-score](https://github.com/neulab/code-bert-score), but can be used for any other model or task.

For more information, see: [https://github.com/neulab/code-bert-score](https://github.com/neulab/code-bert-score)

## Citation

If you use this model for research, please cite:
```
@article{zhou2023codebertscore,
  url = {https://arxiv.org/abs/2302.05527},
  author = {Zhou, Shuyan and Alon, Uri and Agarwal, Sumit and Neubig, Graham},
  title = {CodeBERTScore: Evaluating Code Generation with Pretrained Models of Code},  
  publisher = {arXiv},
  year = {2023},
}
```