
## MLRoBERTa (RoBERTa pretrained on ML Papers)

## How to use:
```
from transformers import AutoTokenizer, AutoModel
tok = AutoTokenizer.from_pretrained('shrutisingh/MLRoBERTa')
model = AutoModel.from_pretrained('shrutisingh/MLRoBERTa')
```

## Pretraining Details:
This is a RoBERTa model trained on scientific documents. The dataset is composed of NeurIPS (1987-2019), CVPR (2013-2020), ICLR (2016-2020), ACL Anthology data (till 2019) paper title and abstracts, and ICLR paper reviews.

## Citation:
```
@inproceedings{singh2021compare,
  title={COMPARE: a taxonomy and dataset of comparison discussions in peer reviews},
  author={Singh, Shruti and Singh, Mayank and Goyal, Pawan},
  booktitle={2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)},
  pages={238--241},
  year={2021},
  organization={IEEE}
}
```
{"language": ["en"], "license": "apache-2.0", "tags": ["Machine Learning", "Research Papers", "Scientific Language Model"]}
transformers pytorch roberta fill-mask Machine Learning Research Papers Scientific Language Model en license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #fill-mask #Machine Learning #Research Papers #Scientific Language Model #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 


## MLRoBERTa (RoBERTa pretrained on ML Papers)

## How to use:


## Pretraining Details:
This is a RoBERTa model trained on scientific documents. The dataset is composed of NeurIPS (1987-2019), CVPR (2013-2020), ICLR (2016-2020), ACL Anthology data (till 2019) paper title and abstracts, and ICLR paper reviews.

:

## MLRoBERTa (RoBERTa pretrained on ML Papers) ## How to use: ## Pretraining Details:
This is a RoBERTa model trained on scientific documents. The dataset is composed of NeurIPS (1987-2019), CVPR (2013-2020), ICLR (2016-2020), ACL Anthology data (till 2019) paper title and abstracts, and ICLR paper reviews.

:
TAGS
#transformers #pytorch #roberta #fill-mask #Machine Learning #Research Papers #Scientific Language Model #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ## MLRoBERTa (RoBERTa pretrained on ML Papers) ## How to use: ## Pretraining Details:
This is a RoBERTa model trained on scientific documents. The dataset is composed of NeurIPS (1987-2019), CVPR (2013-2020), ICLR (2016-2020), ACL Anthology data (till 2019) paper title and abstracts, and ICLR paper reviews.

:
TAGS
#transformers #pytorch #roberta #fill-mask #Machine Learning #Research Papers #Scientific Language Model #en #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
## MLRoBERTa (RoBERTa pretrained on ML Papers)## How to use:## Pretraining Details:
This is a RoBERTa model trained on scientific documents. The dataset is composed of NeurIPS (1987-2019), CVPR (2013-2020), ICLR (2016-2020), ACL Anthology data (till 2019) paper title and abstracts, and ICLR paper reviews.

: