Instructions to use kohils/Twitter-Cyberbullying-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use kohils/Twitter-Cyberbullying-Classification with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("kohils/Twitter-Cyberbullying-Classification", "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
- Xet hash:
- c57eed3c68f000d1ca4b31577ac260ea9935f411191569f36e11b52288d3ef2d
- Size of remote file:
- 85.6 MB
- SHA256:
- 09e56813e9cee53e66aba1fe022b2af62fffe797115e5bb2cb4e053697c544e4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.