Tabular Classification
Scikit-learn
logistic-regression
ai-governance
model-card
fairlearn
public-sector
outreach
fairness
Instructions to use dr-lt/reachfirstmodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use dr-lt/reachfirstmodel with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("dr-lt/reachfirstmodel", "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 Model-Card_Chen-exemplar.pdf from dr-lt/reachfirstmodel: direct link, hf CLI and curl.
- Browser
- Download file 148 kB
-
https://huggingface.co/dr-lt/reachfirstmodel/resolve/main/Model-Card_Chen-exemplar.pdf
- Command line
-
hf download hf://dr-lt/reachfirstmodel/Model-Card_Chen-exemplar.pdf
-
curl -L -o Model-Card_Chen-exemplar.pdf https://huggingface.co/dr-lt/reachfirstmodel/resolve/main/Model-Card_Chen-exemplar.pdf
148 kB
- Xet hash:
- b1d58bdd30391cb4476d1473ec33b2c484dccb774ed35bdcf43d9e834b6e253e
- Size of remote file:
- 148 kB
- SHA256:
- 63d2d217117e018f0f054af1bc858b45aea235b18dbe7b62265ba9cf3f68714c
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