|
--- |
|
license: cc-by-nc-4.0 |
|
--- |
|
|
|
## Model Specification |
|
- This is the **Republican** community GPT-2 language model, fine-tuned on 4.7M (~100M tokens) tweets of Republican Twitter users between 2019-01-01 and 2020-04-10. |
|
- For more details about the `CommunityLM` project, please refer to this [our paper](https://arxiv.org/abs/2209.07065) and [github](https://github.com/hjian42/communitylm) page. |
|
- In the paper, it is referred as the `Fine-tuned CommunityLM` for the Republican Twitter community. |
|
|
|
## How to use the model |
|
|
|
- **PRE-PROCESSING**: when you apply the model on tweets, please make sure that tweets are preprocessed by the [TweetTokenizer](https://github.com/VinAIResearch/BERTweet/blob/master/TweetNormalizer.py) to get the best performance. |
|
|
|
```python |
|
from transformers import AutoTokenizer, AutoModelForCausalLM |
|
|
|
tokenizer = AutoTokenizer.from_pretrained("CommunityLM/republican-twitter-gpt2") |
|
|
|
model = AutoModelForCausalLM.from_pretrained("CommunityLM/republican-twitter-gpt2") |
|
``` |
|
|
|
## References |
|
|
|
If you use this repository in your research, please kindly cite [our paper](https://arxiv.org/abs/2209.07065): |
|
|
|
```bibtex |
|
@inproceedings{jiang-etal-2022-communitylm, |
|
title = "CommunityLM: Probing Partisan Worldviews from Language Models", |
|
author = {Jiang, Hang and Beeferman, Doug and Roy, Brandon and Roy, Deb}, |
|
booktitle = "Proceedings of the 29th International Conference on Computational Linguistics", |
|
year = "2022", |
|
publisher = "International Committee on Computational Linguistics", |
|
} |
|
``` |
