Instructions to use Ma120/Fake-News-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use Ma120/Fake-News-Detection with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("Ma120/Fake-News-Detection", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
Download fake_news_pipeline.skops from Ma120/Fake-News-Detection: direct link, hf CLI and curl.
- Browser
- Download file 71.3 MB
-
https://huggingface.co/Ma120/Fake-News-Detection/resolve/main/fake_news_pipeline.skops
- Command line
-
hf download hf://Ma120/Fake-News-Detection/fake_news_pipeline.skops
-
curl -L -o fake_news_pipeline.skops https://huggingface.co/Ma120/Fake-News-Detection/resolve/main/fake_news_pipeline.skops
71.3 MB
- Xet hash:
- 2fc959cf777fa81420f24d383e74dcada5eaff81d2ab3cc5014292abe2771389
- Size of remote file:
- 71.3 MB
- SHA256:
- 340163893b80499e0a9288e386446b075c79a60685b32b1c4333234c2309be10
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.