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 saved_model.pb from ad2024/recommender-model: direct link, hf CLI and curl.
- Browser
- Download file 104 kB
-
https://huggingface.co/ad2024/recommender-model/resolve/main/saved_model.pb
- Command line
-
hf download hf://ad2024/recommender-model/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/ad2024/recommender-model/resolve/main/saved_model.pb
104 kB
- Xet hash:
- 417fd98b40da84266b319a7718958e08e7ec1018f50d3db8765207aa0aafe86c
- Size of remote file:
- 104 kB
- SHA256:
- 11ed5fab6b4866e77e9bc26e7104aa784038a203a6d920b8f9bd1840b7774259
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