pytorch tf jax roberta arxiv:2002.08155 transformers
.gitattributes README.md config.json flax_model.msgpack merges.txt pytorch_model.bin special_tokens_map.json tf_model.h5 tokenizer_config.json vocab.json
## CodeBERT-base
Pretrained weights for [CodeBERT: A Pre-Trained Model for Programming and Natural Languages](https://arxiv.org/abs/2002.08155).

### Training Data
The model is trained on bi-modal data (documents & code) of [CodeSearchNet](https://github.com/github/CodeSearchNet)

### Training Objective
This model is initialized with Roberta-base and trained with MLM+RTD objective (cf. the paper).

### Usage
Please see [the official repository](https://github.com/microsoft/CodeBERT) for scripts that support "code search" and "code-to-document generation".

### Reference
1. [CodeBERT trained with Masked LM objective](https://huggingface.co/microsoft/codebert-base-mlm) (suitable for code completion)
2. 🤗 [Hugging Face's CodeBERTa](https://huggingface.co/huggingface/CodeBERTa-small-v1) (small size, 6 layers)

### Citation
```bibtex
@misc{feng2020codebert,
    title={CodeBERT: A Pre-Trained Model for Programming and Natural Languages},
    author={Zhangyin Feng and Daya Guo and Duyu Tang and Nan Duan and Xiaocheng Feng and Ming Gong and Linjun Shou and Bing Qin and Ting Liu and Daxin Jiang and Ming Zhou},
    year={2020},
    eprint={2002.08155},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}
```
