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
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Download README_TEMPLATE.md from dr-lt/reachfirstmodel: direct link, hf CLI and curl.
- Browser
- Download file 1.03 kB
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https://huggingface.co/dr-lt/reachfirstmodel/resolve/main/README_TEMPLATE.md
- Command line
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hf download hf://dr-lt/reachfirstmodel/README_TEMPLATE.md
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curl -L -o README_TEMPLATE.md https://huggingface.co/dr-lt/reachfirstmodel/resolve/main/README_TEMPLATE.md
1.03 kB
| license: cc-by-4.0 | |
| library_name: sklearn | |
| pipeline_tag: tabular-classification | |
| tags: | |
| - tabular-classification | |
| - ai-governance | |
| - model-card | |
| datasets: | |
| - YOUR-ACCOUNT/reachfirst-data | |
| # Model Card: ReachFirst v1 (Crosswind Workforce Partnership) | |
| **Governance analyst:** [YOUR NAME] | |
| **Program:** AI Governance Practicum, Track 1, cohort 1 | |
| The model card for ReachFirst v1, the version the Chief AI Officer signed in Week 6, is the PDF in this repository: [Model-Card.pdf](Model-Card.pdf). | |
| The signed model file and its SHA-256 are in the program's model repository, [drdavidprivacy/reachfirst-model](https://huggingface.co/drdavidprivacy/reachfirst-model), and the running model is the program's Space, [drdavidprivacy/reachfirst](https://huggingface.co/spaces/drdavidprivacy/reachfirst). The data is documented in [YOUR-ACCOUNT/reachfirst-data](https://huggingface.co/datasets/YOUR-ACCOUNT/reachfirst-data). | |
| *The organization, the system, and the people are fictional. The data is public. Educational use only.* | |