Instructions to use funlab/clipnet-fold_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use funlab/clipnet-fold_4 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://funlab/clipnet-fold_4") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from funlab/clipnet-fold_4: direct link, hf CLI and curl.
- Browser
- Download file 1.37 MB
-
https://huggingface.co/funlab/clipnet-fold_4/resolve/main/saved_model.pb
- Command line
-
hf download hf://funlab/clipnet-fold_4/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/funlab/clipnet-fold_4/resolve/main/saved_model.pb
1.37 MB
- Xet hash:
- b062f3295992f85e4a5ac37b3c6e146f2738e5919524833dd22f239af60d5f20
- Size of remote file:
- 1.37 MB
- SHA256:
- e12972a1711618416b3664fc417b1a5da1ac9458b38c475125f78a6a5681801d
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