Instructions to use sgonzalezsilot/FakeNewsDetection_Constraint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgonzalezsilot/FakeNewsDetection_Constraint with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sgonzalezsilot/FakeNewsDetection_Constraint")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sgonzalezsilot/FakeNewsDetection_Constraint") model = AutoModelForSequenceClassification.from_pretrained("sgonzalezsilot/FakeNewsDetection_Constraint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sgonzalezsilot/FakeNewsDetection_Constraint: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/sgonzalezsilot/FakeNewsDetection_Constraint/resolve/main/training_args.bin
- Command line
-
hf download hf://sgonzalezsilot/FakeNewsDetection_Constraint/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sgonzalezsilot/FakeNewsDetection_Constraint/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- 74a93365929292057c02e3085e6667a9c5eedba4e47d99e36d1ef5cb9485ccdc
- Size of remote file:
- 4.66 kB
- SHA256:
- 45b5a7ec7d3b5b7a1e843e0dfd0f5a62e3fb89441dfe4abee884f260f2d63c39
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