Instructions to use ICFgainAI/Section with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ICFgainAI/Section 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://ICFgainAI/Section") - Notebooks
- Google Colab
- Kaggle
Download base_mat_scaler.pkl from ICFgainAI/Section: direct link, hf CLI and curl.
- Browser
- Download file 13.5 kB
-
https://huggingface.co/ICFgainAI/Section/resolve/main/base_mat_scaler.pkl
- Command line
-
hf download hf://ICFgainAI/Section/base_mat_scaler.pkl
-
curl -L -o base_mat_scaler.pkl https://huggingface.co/ICFgainAI/Section/resolve/main/base_mat_scaler.pkl
13.5 kB
- Xet hash:
- 878b18327a4f571a802d15d28bf21c69fb28df2312bcfb4ff5b33294082dfdcc
- Size of remote file:
- 13.5 kB
- SHA256:
- dd375c96ba644df10df805e379e670acc10a58638c5dafbd131b2f9cfce3fa3a
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