Text Classification
Transformers
Safetensors
Vietnamese
bert
clickbait-detection
vietnamese
viclickbait-2025
text-embeddings-inference
Instructions to use BaoNhan/mbert-ViClickbait-2025 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BaoNhan/mbert-ViClickbait-2025 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BaoNhan/mbert-ViClickbait-2025")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BaoNhan/mbert-ViClickbait-2025") model = AutoModelForSequenceClassification.from_pretrained("BaoNhan/mbert-ViClickbait-2025", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 620290bcea3935ce3ab099c67fae987dd65e642405d7cd23f89c5dfdfcc62b95
- Size of remote file:
- 5.43 kB
- SHA256:
- f64dd799b023117e5d5316a018e21e6a7d288253338abb5eb19b8066a9e07be7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.