Instructions to use keras-io/conv-lstm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use keras-io/conv-lstm 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("keras-io/conv-lstm") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from keras-io/conv-lstm: direct link, hf CLI and curl.
- Browser
- Download file 1.09 MB
-
https://huggingface.co/keras-io/conv-lstm/resolve/main/saved_model.pb
- Command line
-
hf download hf://keras-io/conv-lstm/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/keras-io/conv-lstm/resolve/main/saved_model.pb
1.09 MB
- Xet hash:
- 2741eb23785bf690b99208e40e4683628ebe5c68513a46eea40b9efd42378157
- Size of remote file:
- 1.09 MB
- SHA256:
- 6a0eb6039b2ba8b67b02b779e7fdb5e55c7d3692d50473cd13420c929aa294d8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.