Instructions to use funlab/clipnet-fold_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use funlab/clipnet-fold_1 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_1") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from funlab/clipnet-fold_1: direct link, hf CLI and curl.
- Browser
- Download file 1.37 MB
-
https://huggingface.co/funlab/clipnet-fold_1/resolve/refs%2Fpr%2F1/saved_model.pb
- Command line
-
hf download hf://funlab/clipnet-fold_1@refs/pr/1/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/funlab/clipnet-fold_1/resolve/refs%2Fpr%2F1/saved_model.pb
1.37 MB
- Xet hash:
- bde3c9444f19c7f5b96e06816bb91e051f16bdb861285a856ca5b37d30cc87f6
- Size of remote file:
- 1.37 MB
- SHA256:
- f2d37e3b5abdea732392b0b896b5b5e9050d721f7cc4a4049ab56178f8db0742
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