Instructions to use hqasmei/collaborative-filtering-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use hqasmei/collaborative-filtering-model with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://hqasmei/collaborative-filtering-model") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from hqasmei/collaborative-filtering-model: direct link, hf CLI and curl.
- Browser
- Download file 112 kB
-
https://huggingface.co/hqasmei/collaborative-filtering-model/resolve/main/saved_model.pb
- Command line
-
hf download hf://hqasmei/collaborative-filtering-model/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/hqasmei/collaborative-filtering-model/resolve/main/saved_model.pb
112 kB
- Xet hash:
- 0a893b4d1ac8fb52565ff48e8f163186ddf49f7542168b91430aa1ff05576b55
- Size of remote file:
- 112 kB
- SHA256:
- b21e8aee39fb8199c296be584aae9a71999340fce3a5cc8e8cbdeb555f26025b
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