Instructions to use imaflower/dienbien-rice-yield with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use imaflower/dienbien-rice-yield with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("imaflower/dienbien-rice-yield", "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:
- 88820f65999cdb05fe0244988ffad337ce6c5de9e5a18f4233ad309b9e55fcc9
- Size of remote file:
- 6.64 MB
- SHA256:
- 653daf3a7ac6f76242fbeca37f45cc76b6f4b3210390b54bba14a049958eb853
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.