Instructions to use svanhvit/formality-classification-icebert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use svanhvit/formality-classification-icebert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="svanhvit/formality-classification-icebert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("svanhvit/formality-classification-icebert") model = AutoModelForSequenceClassification.from_pretrained("svanhvit/formality-classification-icebert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 517eb913ef14db0cafcc04423373a0d6efe73f83febe8c042a3e931f084dae6b
- Size of remote file:
- 498 MB
- SHA256:
- 5507700044cbc870111366df7ae321200fa15cf76246da729f665619c35e759d
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