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/fingerprint.pb from Jabka/Neue_Model: direct link, hf CLI and curl.
- Browser
- Download file 55 Bytes
-
https://huggingface.co/Jabka/Neue_Model/resolve/main/my_model/fingerprint.pb
- Command line
-
hf download hf://Jabka/Neue_Model/my_model/fingerprint.pb
-
curl -L -o fingerprint.pb https://huggingface.co/Jabka/Neue_Model/resolve/main/my_model/fingerprint.pb
55 Bytes
- Xet hash:
- b28239f7c997ca1fa11a6a25af87b8e7c1b3b94318292d0724ec273c97d64ee5
- Size of remote file:
- 55 Bytes
- SHA256:
- fd604f1ae0f5b0d4da3509c3c129326f44457b4276e5c37fbcd9f52f920f2641
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