Instructions to use clfegg/content_based_recommend with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use clfegg/content_based_recommend with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import ContentBasedRecommender model = ContentBasedRecommender.from_pretrained("clfegg/content_based_recommend", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.pkl from clfegg/content_based_recommend: direct link, hf CLI and curl.
- Browser
- Download file 232 MB
-
https://huggingface.co/clfegg/content_based_recommend/resolve/main/model.pkl
- Command line
-
hf download hf://clfegg/content_based_recommend/model.pkl
-
curl -L -o model.pkl https://huggingface.co/clfegg/content_based_recommend/resolve/main/model.pkl
232 MB
- Xet hash:
- 902ad7e252781ba139d1d0e4359a586588176782856300518d33d12ae7df9875
- Size of remote file:
- 232 MB
- SHA256:
- 4546a9c17e3c7fefce8aed1d569c4208eebb73a4dfbe0b8e838ff28ca2967201
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