Instructions to use bdr-ai-org/insurance-claims-decision-model-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use bdr-ai-org/insurance-claims-decision-model-v1 with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("bdr-ai-org/insurance-claims-decision-model-v1", "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 accident_type_encoder.pkl from bdr-ai-org/insurance-claims-decision-model-v1: direct link, hf CLI and curl.
- Browser
- Download file 516 Bytes
-
https://huggingface.co/bdr-ai-org/insurance-claims-decision-model-v1/resolve/main/accident_type_encoder.pkl
- Command line
-
hf download hf://bdr-ai-org/insurance-claims-decision-model-v1/accident_type_encoder.pkl
-
curl -L -o accident_type_encoder.pkl https://huggingface.co/bdr-ai-org/insurance-claims-decision-model-v1/resolve/main/accident_type_encoder.pkl
516 Bytes
- Xet hash:
- f7974c1b39955c1d1397c02824a80da11f2574161321d19178211f09daf88464
- Size of remote file:
- 516 Bytes
- SHA256:
- 89f10add23da3b01a24857d73d0ee99ee5a6a05bb20cc882719b8ce576e5658d
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