Instructions to use usmiva/bert-deepfake-bg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use usmiva/bert-deepfake-bg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="usmiva/bert-deepfake-bg")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("usmiva/bert-deepfake-bg") model = AutoModelForSequenceClassification.from_pretrained("usmiva/bert-deepfake-bg") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 357d48b0a4c16f2d21cd129127fe56e47ae1b1b20c7e0cde6a4ca1ad19b0a310
- Size of remote file:
- 873 MB
- SHA256:
- 993b9cf72dad14dc5045d358035d3852573270e6374e90370368c1078d18f0c7
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