Instructions to use monkseal555/GANMay24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use monkseal555/GANMay24 with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("monkseal555/GANMay24") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from monkseal555/GANMay24: direct link, hf CLI and curl.
- Browser
- Download file 1.01 MB
-
https://huggingface.co/monkseal555/GANMay24/resolve/main/saved_model.pb
- Command line
-
hf download hf://monkseal555/GANMay24/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/monkseal555/GANMay24/resolve/main/saved_model.pb
1.01 MB
- Xet hash:
- 3212682cd897ef91755d98271f0753998e60caafdc9c2ef6f65f1cadef949acf
- Size of remote file:
- 1.01 MB
- SHA256:
- 0f0c61bbc7804efe93bc213b94d256b1f36f3f0d4b8e5c8eec0ccdac3442b289
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.