Instructions to use Danieltash0/dairydan-yield-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use Danieltash0/dairydan-yield-models with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("Danieltash0/dairydan-yield-models", "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 coldstart_preprocessor.joblib from Danieltash0/dairydan-yield-models: direct link, hf CLI and curl.
- Browser
- Download file 6.34 kB
-
https://huggingface.co/Danieltash0/dairydan-yield-models/resolve/main/coldstart_preprocessor.joblib
- Command line
-
hf download hf://Danieltash0/dairydan-yield-models/coldstart_preprocessor.joblib
-
curl -L -o coldstart_preprocessor.joblib https://huggingface.co/Danieltash0/dairydan-yield-models/resolve/main/coldstart_preprocessor.joblib
6.34 kB
- Xet hash:
- fbac7823f8dd4b470d80c4ac0b9f4fb3ab8530ff6224971cb6ae4e0a5df9a20c
- Size of remote file:
- 6.34 kB
- SHA256:
- ff5bfe638f9e2ceefc3a9457cc4401cd67be61e2e4e3726f4abf3d5d821a7456
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