Instructions to use mindwrapped/collaborative-filtering-movielens-copy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use mindwrapped/collaborative-filtering-movielens-copy with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://mindwrapped/collaborative-filtering-movielens-copy") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b76f785a5ade3c85806daafaf466ffdfd41df6de7176acd3fc5ffb012b751f9
- Size of remote file:
- 121 kB
- SHA256:
- a900821259edc62b7a54c23fc83d81244f32a48ff276ce8b68419840568f918f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.