

# BERTOverflow

## Model description

We pre-trained BERT-base model on 152 million sentences from the StackOverflow's 10 year archive. More details of this model can be found in our ACL 2020 paper: [Code and Named Entity Recognition in StackOverflow](https://www.aclweb.org/anthology/2020.acl-main.443/). We would like to thank [Wuwei Lan](https://lanwuwei.github.io/) for helping us in training this model. 




#### How to use

```python
from transformers import *
import torch

tokenizer = AutoTokenizer.from_pretrained("jeniya/BERTOverflow")
model = AutoModelForTokenClassification.from_pretrained("jeniya/BERTOverflow")

```



### BibTeX entry and citation info

```bibtex
@inproceedings{tabassum2020code,
    title={Code and Named Entity Recognition in StackOverflow},
    author={Tabassum, Jeniya  and Maddela, Mounica  and Xu, Wei and Ritter, Alan },
    booktitle = {Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL)},
    url={https://www.aclweb.org/anthology/2020.acl-main.443/}
    year = {2020},
}
```
{}
transformers pytorch jax bert feature-extraction endpoints_compatible region:us
TAGS
#transformers #pytorch #jax #bert #feature-extraction #endpoints_compatible #region-us 



# BERTOverflow

## Model description

We pre-trained BERT-base model on 152 million sentences from the StackOverflow's 10 year archive. More details of this model can be found in our ACL 2020 paper: Code and Named Entity Recognition in StackOverflow. We would like to thank Wuwei Lan for helping us in training this model. 




#### How to use





### BibTeX entry and citation info


# BERTOverflow ## Model description

We pre-trained BERT-base model on 152 million sentences from the StackOverflow's 10 year archive. More details of this model can be found in our ACL 2020 paper: Code and Named Entity Recognition in StackOverflow. We would like to thank Wuwei Lan for helping us in training this model. #### How to use ### BibTeX entry and citation info
TAGS
#transformers #pytorch #jax #bert #feature-extraction #endpoints_compatible #region-us 
 # BERTOverflow ## Model description

We pre-trained BERT-base model on 152 million sentences from the StackOverflow's 10 year archive. More details of this model can be found in our ACL 2020 paper: Code and Named Entity Recognition in StackOverflow. We would like to thank Wuwei Lan for helping us in training this model. #### How to use ### BibTeX entry and citation info
passage: TAGS
#transformers #pytorch #jax #bert #feature-extraction #endpoints_compatible #region-us 
# BERTOverflow## Model description

We pre-trained BERT-base model on 152 million sentences from the StackOverflow's 10 year archive. More details of this model can be found in our ACL 2020 paper: Code and Named Entity Recognition in StackOverflow. We would like to thank Wuwei Lan for helping us in training this model.#### How to use### BibTeX entry and citation info