Fill-Mask
Transformers
PyTorch
English
roberta
twitter
masked-token-prediction
bertweet
election2020
politics
Instructions to use kornosk/polibertweet-political-twitter-roberta-mlm-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kornosk/polibertweet-political-twitter-roberta-mlm-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="kornosk/polibertweet-political-twitter-roberta-mlm-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("kornosk/polibertweet-political-twitter-roberta-mlm-small") model = AutoModelForMaskedLM.from_pretrained("kornosk/polibertweet-political-twitter-roberta-mlm-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
This version is trained on a smaller data set.
See the full-size version at PoliBERTweet.
Citation
@inproceedings{kawintiranon2022polibertweet,
title = {PoliBERTweet: A Pre-trained Language Model for Analyzing Political Content on Twitter},
author = {Kawintiranon, Kornraphop and Singh, Lisa},
booktitle = {Proceedings of the Language Resources and Evaluation Conference},
year = {2022},
publisher = {European Language Resources Association}
}
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