Instructions to use pinecone/movie-recommender-user-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use pinecone/movie-recommender-user-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://pinecone/movie-recommender-user-model") - Notebooks
- Google Colab
- Kaggle
Download model.png from pinecone/movie-recommender-user-model: direct link, hf CLI and curl.
- Browser
- Download file 5.47 kB
-
https://huggingface.co/pinecone/movie-recommender-user-model/resolve/main/model.png
- Command line
-
hf download hf://pinecone/movie-recommender-user-model/model.png
-
curl -L -o model.png https://huggingface.co/pinecone/movie-recommender-user-model/resolve/main/model.png
5.47 kB

- Xet hash:
- 517c2b68ab19781b22725d984fd0acb03716a966538a2d0e934d4e55f22f7eb4
- Size of remote file:
- 5.47 kB
- SHA256:
- f2a25034094d4060c4faa7aeccdf4029fe8811e0eb5a03b2bcaa82d7b68e9f16
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