Instructions to use Jabka/Neue_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Jabka/Neue_Model 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://Jabka/Neue_Model") - Notebooks
- Google Colab
- Kaggle
Download my_model/keras_metadata.pb from Jabka/Neue_Model: direct link, hf CLI and curl.
- Browser
- Download file 15.7 kB
-
https://huggingface.co/Jabka/Neue_Model/resolve/main/my_model/keras_metadata.pb
- Command line
-
hf download hf://Jabka/Neue_Model/my_model/keras_metadata.pb
-
curl -L -o keras_metadata.pb https://huggingface.co/Jabka/Neue_Model/resolve/main/my_model/keras_metadata.pb
15.7 kB
- Xet hash:
- d5886c7adff55cc7f4bc6b376ae887a757a229fa4a3af830578da07aae6258d3
- Size of remote file:
- 15.7 kB
- SHA256:
- 6cf3e0542f674e64cf876f1f0d0137382573b30c1ffdd69602a9f0c4fadfc4e3
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