Instructions to use Denyol/FakeNews-roberta-base-html with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Denyol/FakeNews-roberta-base-html with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Denyol/FakeNews-roberta-base-html")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Denyol/FakeNews-roberta-base-html") model = AutoModelForSequenceClassification.from_pretrained("Denyol/FakeNews-roberta-base-html", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Denyol/FakeNews-roberta-base-html: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Denyol/FakeNews-roberta-base-html/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Denyol/FakeNews-roberta-base-html/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Denyol/FakeNews-roberta-base-html/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- fce9677c8456bcaed415448265f7bfc2898bea51a002717597ad8968b0cc4ce9
- Size of remote file:
- 499 MB
- SHA256:
- 5ebf5e3e64bbc24481422e41172a14c39990527398497742e5aa4093ce68cfef
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