Instructions to use ChristianTeroerde/modelscan-nested-lambda-poc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ChristianTeroerde/modelscan-nested-lambda-poc 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://ChristianTeroerde/modelscan-nested-lambda-poc") - Notebooks
- Google Colab
- Kaggle
Download nested-wrapper-lambda.h5 from ChristianTeroerde/modelscan-nested-lambda-poc: direct link, hf CLI and curl.
- Browser
- Download file 9.22 kB
-
https://huggingface.co/ChristianTeroerde/modelscan-nested-lambda-poc/resolve/main/nested-wrapper-lambda.h5
- Command line
-
hf download hf://ChristianTeroerde/modelscan-nested-lambda-poc/nested-wrapper-lambda.h5
-
curl -L -o nested-wrapper-lambda.h5 https://huggingface.co/ChristianTeroerde/modelscan-nested-lambda-poc/resolve/main/nested-wrapper-lambda.h5
9.22 kB
- Xet hash:
- 3398838ab194297741bb9ddb4b18b45ef756f71d51560481ee70e321d4232694
- Size of remote file:
- 9.22 kB
- SHA256:
- f218fcaa1e36d10f85c44364be6e228b9943962c663d183783af5502f10ed833
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