Instructions to use JackVines/ds_saliency_inference with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use JackVines/ds_saliency_inference 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("JackVines/ds_saliency_inference") - Notebooks
- Google Colab
- Kaggle
Download app/saved_model.pb from JackVines/ds_saliency_inference: direct link, hf CLI and curl.
- Browser
- Download file 99.9 MB
-
https://huggingface.co/JackVines/ds_saliency_inference/resolve/main/app/saved_model.pb
- Command line
-
hf download hf://JackVines/ds_saliency_inference/app/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/JackVines/ds_saliency_inference/resolve/main/app/saved_model.pb
99.9 MB
- Xet hash:
- 5fc6aba5067ba23cc94865330c22e98289e7f571f9abf162ff0859dcfb5c9f16
- Size of remote file:
- 99.9 MB
- SHA256:
- 646e0f343c4357e828f2569bef2f2bf288449fe68f7e4fb43e076f2e3b094e3d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.