Instructions to use hanseokhyeon/bert-badword with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hanseokhyeon/bert-badword with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hanseokhyeon/bert-badword")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hanseokhyeon/bert-badword") model = AutoModelForSequenceClassification.from_pretrained("hanseokhyeon/bert-badword") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1f0a1d5cfd8ccf5aeebaa276cb654ed719303dadb89fdca418f41d73b2b88be
- Size of remote file:
- 1.34 GB
- SHA256:
- b54498ae6feb7349dc805162c6bdc2e02828280ea685355501fe0a86ed721ca1
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