Text Classification
Transformers
Safetensors
Vietnamese
bert
vietnamese
fact-checking
claim-verification
natural-language-inference
vifactcheck
gold-evidence
eacl-2027
Instructions to use BaoNhan/wikibert-ViFactCheck-GE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BaoNhan/wikibert-ViFactCheck-GE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BaoNhan/wikibert-ViFactCheck-GE")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BaoNhan/wikibert-ViFactCheck-GE") model = AutoModelForSequenceClassification.from_pretrained("BaoNhan/wikibert-ViFactCheck-GE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f75684e21f52b539dbc12fb9dc1e8b9bcb1291c0515d93edf9db949f20f6df5b
- Size of remote file:
- 5.5 kB
- SHA256:
- 27c3751c7a8d11dc64f9b60afe93280ad4faf93ce98a6d78a9c97ec8394c8b66
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