Instructions to use ad2024/recommender-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use ad2024/recommender-model 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("ad2024/recommender-model") - Notebooks
- Google Colab
- Kaggle
Download keras_metadata.pb from ad2024/recommender-model: direct link, hf CLI and curl.
- Browser
- Download file 5.77 kB
-
https://huggingface.co/ad2024/recommender-model/resolve/main/keras_metadata.pb
- Command line
-
hf download hf://ad2024/recommender-model/keras_metadata.pb
-
curl -L -o keras_metadata.pb https://huggingface.co/ad2024/recommender-model/resolve/main/keras_metadata.pb
5.77 kB
- Xet hash:
- 6cb516606248afaebaff4d86aefbf25e0ec63881047222a9c620cce9646ac9d0
- Size of remote file:
- 5.77 kB
- SHA256:
- dd9f68690243bccc083daac230ac0a3237fb7a2bfe3eded2800a9de2769ea4d8
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