Instructions to use KalsusEvening/Melbourne_Housing_Regression with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use KalsusEvening/Melbourne_Housing_Regression with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("KalsusEvening/Melbourne_Housing_Regression", "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 07_elbow_method.png from KalsusEvening/Melbourne_Housing_Regression: direct link, hf CLI and curl.
- Browser
- Download file 102 kB
-
https://huggingface.co/KalsusEvening/Melbourne_Housing_Regression/resolve/main/07_elbow_method.png
- Command line
-
hf download hf://KalsusEvening/Melbourne_Housing_Regression/07_elbow_method.png
-
curl -L -o 07_elbow_method.png https://huggingface.co/KalsusEvening/Melbourne_Housing_Regression/resolve/main/07_elbow_method.png
102 kB

- Xet hash:
- ba6314f86e7d7cf62593e2df8bde782bf56fcdd1a0b05942436dea9243f9016e
- Size of remote file:
- 102 kB
- SHA256:
- 39f8a5bac534cdf79ecd521019bcc8022cd89ae00f21b8b2a50f74893e7eee19
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