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 y_scaler.pkl from ICFgainAI/Section: direct link, hf CLI and curl.
- Browser
- Download file 719 Bytes
-
https://huggingface.co/ICFgainAI/Section/resolve/main/y_scaler.pkl
- Command line
-
hf download hf://ICFgainAI/Section/y_scaler.pkl
-
curl -L -o y_scaler.pkl https://huggingface.co/ICFgainAI/Section/resolve/main/y_scaler.pkl
719 Bytes
- Xet hash:
- b70c1edc19c8fc901d156fa8c0bb44082b87726fe2a2decd80c775074de339fa
- Size of remote file:
- 719 Bytes
- SHA256:
- 60ff26e0838461c0efb36a7218d70ac82934db6d3bd774e51022b012e474d786
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