Instructions to use acappella/FakeNewsClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use acappella/FakeNewsClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="acappella/FakeNewsClassifier")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("acappella/FakeNewsClassifier") model = AutoModel.from_pretrained("acappella/FakeNewsClassifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3654afebc8102b591b856cf9aa18cd3f8fbbacafa3e256f62ca12b88914f2be8
- Size of remote file:
- 438 MB
- SHA256:
- ff8e66bc015553d84e94959a0b84aa7386b59a83ae74b49189f735b107b01afc
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