Instructions to use Cameron/BERT-SBIC-offensive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cameron/BERT-SBIC-offensive with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cameron/BERT-SBIC-offensive")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cameron/BERT-SBIC-offensive") model = AutoModelForSequenceClassification.from_pretrained("Cameron/BERT-SBIC-offensive", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b36890e1ae5a19f4aee44059f38e5a3e28d7e22319711c325573fbd26cffc90
- Size of remote file:
- 867 MB
- SHA256:
- a205c2f665fa563cd149e69ccbd1088373daec6315cc672b7e8f53e6d68d3ab7
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