Instructions to use imshriya/mlforge-testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use imshriya/mlforge-testing with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("imshriya/mlforge-testing", "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:
- 3da08a09a4585cc096206188bacd0738750394ceff6269d91bc1a22487a0c157
- Size of remote file:
- 1.04 kB
- SHA256:
- 020a7ee59feb0cc785b6b2e996ff56e466696dc8403e66da587bcdcb1473ea47
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.