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bengali-fake-news
armansakif/bengali-fake-news
bengali-fake-news is a summarization model from armansakif. Use it when you need a shorter version of a longer text. It is set up for transformers. The card lists the license as cc-by-nc-sa-4.0.
This is Bengali Fake News detection model, version 1.0. This model was introduced in this paper. An original implementation is deployed in this huggingface space.
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At a glance
- Task
- Summarization
- Library
- transformers
- License
- cc-by-nc-sa-4.0
- Model type
- bert
- Access
- Public
- Created
- Jul 31, 2023
- Updated
- Jul 31, 2023
- SHA
- 07cb1538
Try a prompt
Model card
From the Hugging Face model README
Model Description
This is Bengali Fake News detection model, version 1.0. This model was introduced in this paper. An original implementation is deployed in this huggingface space.
In the hosted API interface on the right, the meaning of labels are: LABEL_0 = Fake LABEL_1 = Authentic
Model type: deep learning classifier
Finetuned From Model : https://huggingface.co/bert-base-multilingual-cased
How to load this model using transformers (tested on 4.31.0-py3)
from transformers import BertTokenizer, AutoTokenizer
from transformers import BertForSequenceClassification, AdamW, BertConfig
tokenizer = AutoTokenizer.from_pretrained('armansakif/bengali-fake-news')
model = BertForSequenceClassification.from_pretrained(
"armansakif/bengali-fake-news", # Use the 12-layer BERT model, with an uncased vocab.
num_labels = 2, # The number of output labels--2 for binary classification.
# You can increase this for multi-class tasks.
output_attentions = False, # Whether the model returns attentions weights.
output_hidden_states = False, # Whether the model returns all hidden-states.
)
Citation
If you use this model, please cite the following paper: BibTeX:
@article{chowdhury2023tackling,
title={Tackling Fake News in Bengali: Unraveling the Impact of Summarization vs. Augmentation on Pre-trained Language Models},
author={Chowdhury, Arman Sakif and Shahariar, GM and Aziz, Ahammed Tarik and Alam, Syed Mohibul and Sheikh, Md Azad and Belal, Tanveer Ahmed},
journal={arXiv preprint arXiv:2307.06979},
year={2023}
}
APA:
Chowdhury, A. S., Shahariar, G. M., Aziz, A. T., Alam, S. M., Sheikh, M. A., & Belal, T. A. (2023). Tackling Fake News in Bengali: Unraveling the Impact of Summarization vs. Augmentation on Pre-trained Language Models. arXiv preprint arXiv:2307.06979.
- Task
- Summarization
- Library
- transformers
- Type
- bert
- License
- cc-by-nc-sa-4.0
- Languages
- bn
- Created
- Jul 31, 2023
- Updated
- Jul 31, 2023