Text Classification
Transformers
Safetensors
Vietnamese
claim_verification
SemViQA
binary-classification
fact-checking
Instructions to use SemViQA/bc-xlmr-viwikifc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SemViQA/bc-xlmr-viwikifc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SemViQA/bc-xlmr-viwikifc")# Load model directly from transformers import ClaimModelForClassification model = ClaimModelForClassification.from_pretrained("SemViQA/bc-xlmr-viwikifc", dtype="auto") - Notebooks
- Google Colab
- Kaggle
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If you use **SemViQA-BC** in your research, please cite:
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```bibtex
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@misc{
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title={SemViQA: A Semantic Question Answering System for Vietnamese Information Fact-Checking},
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author={
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year={2025},
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eprint={2503.00955},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2503.00955},
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}
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```
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If you use **SemViQA-BC** in your research, please cite:
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```bibtex
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@misc{tran2025semviqasemanticquestionanswering,
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title={SemViQA: A Semantic Question Answering System for Vietnamese Information Fact-Checking},
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author={Dien X. Tran and Nam V. Nguyen and Thanh T. Tran and Anh T. Hoang and Tai V. Duong and Di T. Le and Phuc-Lu Le},
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year={2025},
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eprint={2503.00955},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2503.00955},
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}
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```
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