Instructions to use gianma/fakeNewsBERTClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gianma/fakeNewsBERTClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gianma/fakeNewsBERTClassifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gianma/fakeNewsBERTClassifier") model = AutoModelForSequenceClassification.from_pretrained("gianma/fakeNewsBERTClassifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from gianma/fakeNewsBERTClassifier: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/gianma/fakeNewsBERTClassifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://gianma/fakeNewsBERTClassifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gianma/fakeNewsBERTClassifier/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 1f020e2e7381eaadefcb59b65dde577e9df35cb39383e2bd741f0b43e431c11b
- Size of remote file:
- 438 MB
- SHA256:
- 67f9cd5f3a07ccb6a72e85369105efa8c2fe93dedf984cc66d79c43ccd06e0ac
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