Text Classification
Transformers
Safetensors
Vietnamese
xlm-roberta
socialmedia
toxiccomment
classification_toxic_comment
transformer
text-embeddings-inference
Instructions to use UngLong/cafebert-classification-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UngLong/cafebert-classification-ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="UngLong/cafebert-classification-ft")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("UngLong/cafebert-classification-ft") model = AutoModelForSequenceClassification.from_pretrained("UngLong/cafebert-classification-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8db3e1d76f91ef5117f1fd2d4644867c32d89a959ab7697205f647cd4a5ba7d5
- Size of remote file:
- 17.1 MB
- SHA256:
- f070edfde9aae8ad9a9dc8f5448c866346b46f75ea47fbc9204d3620254696f9
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