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 fingerprint.pb from ad2024/recommender-model: direct link, hf CLI and curl.
- Browser
- Download file 56 Bytes
-
https://huggingface.co/ad2024/recommender-model/resolve/main/fingerprint.pb
- Command line
-
hf download hf://ad2024/recommender-model/fingerprint.pb
-
curl -L -o fingerprint.pb https://huggingface.co/ad2024/recommender-model/resolve/main/fingerprint.pb
56 Bytes
- Xet hash:
- 87582f11bf7246631ccf577a7cb4fa706d9c92ca413026417c3072ba753f10cd
- Size of remote file:
- 56 Bytes
- SHA256:
- efdc48716cfa9355e2936482340230d06975d46e6e64da53dc4afc8cc6a75e0f
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