Instructions to use Bisher/fearless-elevator-63 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Bisher/fearless-elevator-63 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://Bisher/fearless-elevator-63") - Notebooks
- Google Colab
- Kaggle
Download checkpoint.model.keras from Bisher/fearless-elevator-63: direct link, hf CLI and curl.
- Browser
- Download file 17.3 GB
-
https://huggingface.co/Bisher/fearless-elevator-63/resolve/main/checkpoint.model.keras
- Command line
-
hf download hf://Bisher/fearless-elevator-63/checkpoint.model.keras
-
curl -L -o checkpoint.model.keras https://huggingface.co/Bisher/fearless-elevator-63/resolve/main/checkpoint.model.keras
17.3 GB
- Xet hash:
- 6cedf0f0c5fc83a533ee44492058ac34735df08014bfa5e79127bc2106bbeabb
- Size of remote file:
- 17.3 GB
- SHA256:
- 9b007b407498d4584f3b479c417e8a9644b312dc52fe42750b3f660f9be1c845
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