Instructions to use keras-io/video-transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use keras-io/video-transformers 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("keras-io/video-transformers") - Notebooks
- Google Colab
- Kaggle
Download model.png from keras-io/video-transformers: direct link, hf CLI and curl.
- Browser
- Download file 48.3 kB
-
https://huggingface.co/keras-io/video-transformers/resolve/main/model.png
- Command line
-
hf download hf://keras-io/video-transformers/model.png
-
curl -L -o model.png https://huggingface.co/keras-io/video-transformers/resolve/main/model.png
48.3 kB

- Xet hash:
- d14410315aa53cba94c8f70b89769c57955b868653790785e9009f1d863404f6
- Size of remote file:
- 48.3 kB
- SHA256:
- 244734f7468b933658214ddc0d11d6c92e6551468cb639791f75992ea1188272
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.