Instructions to use kfahn/mandelbulb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use kfahn/mandelbulb 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://kfahn/mandelbulb") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from kfahn/mandelbulb: direct link, hf CLI and curl.
- Browser
- Download file 20.8 MB
-
https://huggingface.co/kfahn/mandelbulb/resolve/refs%2Fpr%2F1/saved_model.pb
- Command line
-
hf download hf://kfahn/mandelbulb@refs/pr/1/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/kfahn/mandelbulb/resolve/refs%2Fpr%2F1/saved_model.pb
20.8 MB
- Xet hash:
- f54b44b138349dc852163bdc7967ef02d13d5ee77a104eedfed4d9d956099e0d
- Size of remote file:
- 20.8 MB
- SHA256:
- 7e51313fcfef3f4e3e3eda1a3fc6d922893a417fbebf6c06afd3a6ce4997cfb6
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