Text Classification
Keras
Scikit-learn
English
patient-readmission
predictive-model
healthcare
LightGBM
Instructions to use prabinpanta0/Patient-Readmission-Prediction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use prabinpanta0/Patient-Readmission-Prediction with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://prabinpanta0/Patient-Readmission-Prediction") - Scikit-learn
How to use prabinpanta0/Patient-Readmission-Prediction with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("prabinpanta0/Patient-Readmission-Prediction", "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_RandomForestClassifier.pkl from prabinpanta0/Patient-Readmission-Prediction: direct link, hf CLI and curl.
- Browser
- Download file 31.6 MB
-
https://huggingface.co/prabinpanta0/Patient-Readmission-Prediction/resolve/main/model_RandomForestClassifier.pkl
- Command line
-
hf download hf://prabinpanta0/Patient-Readmission-Prediction/model_RandomForestClassifier.pkl
-
curl -L -o model_RandomForestClassifier.pkl https://huggingface.co/prabinpanta0/Patient-Readmission-Prediction/resolve/main/model_RandomForestClassifier.pkl
31.6 MB
- Xet hash:
- 8ad0fc4524046601cf61de3dc3f07151d463c9364905674f73cd9fe6fbc8bb42
- Size of remote file:
- 31.6 MB
- SHA256:
- 7f8835bc58c3a5ca872837e8621f53c5ddbeb6b6ecd8c952604beac2b18fe4b2
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