Text Classification
Transformers
PyTorch
Safetensors
Vietnamese
roberta
transfomer
sbert
legaltext
vietnamese
Instructions to use hmthanh/VietnamLegalText-SBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hmthanh/VietnamLegalText-SBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hmthanh/VietnamLegalText-SBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hmthanh/VietnamLegalText-SBERT") model = AutoModelForSequenceClassification.from_pretrained("hmthanh/VietnamLegalText-SBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9b84992e43ac7727e74aebe7f9a2f4f288e25367c1e01d77d0b51409650d889
- Size of remote file:
- 540 MB
- SHA256:
- dad8a7a7f454be39fa56995a35f8aef42cb4e9018e4913e0d1af7d2cbd32066d
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