Instructions to use prteek/mnist1d_clf_1v7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use prteek/mnist1d_clf_1v7 with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("prteek/mnist1d_clf_1v7", "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 handler.py from prteek/mnist1d_clf_1v7: direct link, hf CLI and curl.
- Browser
- Download file 368 Bytes
-
https://huggingface.co/prteek/mnist1d_clf_1v7/resolve/main/handler.py
- Command line
-
hf download hf://prteek/mnist1d_clf_1v7/handler.py
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curl -L -o handler.py https://huggingface.co/prteek/mnist1d_clf_1v7/resolve/main/handler.py
368 Bytes
| import joblib | |
| import pandas as pd | |
| class EndpointHandler: | |
| def __init__(self, path=""): | |
| self.model = joblib.load(f"{path}/model.joblib") | |
| def __call__(self, data): | |
| # {"inputs": [[x_0, ..., x_39], ...]} | |
| X = pd.DataFrame(data["inputs"], columns=self.model.feature_names_in_) | |
| return {"predictions": self.model.predict(X).tolist()} | |