Instructions to use haipradana/tracko-movinet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use haipradana/tracko-movinet with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("haipradana/tracko-movinet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e17af78bf574e1893bb93de6c3a2e7b47025209b5d6dd6779aec9d13b5d4cb1d
- Size of remote file:
- 77 Bytes
- SHA256:
- a99fe7817d73513112856861105c8aadb46347de628c0b9a18e3f38303d8fa65
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.