Instructions to use recommender-system/impact-p with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use recommender-system/impact-p with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://recommender-system/impact-p") - Notebooks
- Google Colab
- Kaggle
Download Datasets/bundle_data.json.gz from recommender-system/impact-p: direct link, hf CLI and curl.
- Browser
- Download file 91.9 kB
-
https://huggingface.co/recommender-system/impact-p/resolve/main/Datasets/bundle_data.json.gz
- Command line
-
hf download hf://recommender-system/impact-p/Datasets/bundle_data.json.gz
-
curl -L -o bundle_data.json.gz https://huggingface.co/recommender-system/impact-p/resolve/main/Datasets/bundle_data.json.gz
91.9 kB
- Xet hash:
- 20cfbe9c5487e6e870f2065a5d2186a320cebd2502dbfd0244c0d3c3f962ff54
- Size of remote file:
- 91.9 kB
- SHA256:
- fc182cb8e99b4b9781bae2f8a0bb2c7a9cf382c215e1f01e73e2f21291dc2d2f
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