| | --- |
| | license: mit |
| | tags: |
| | - recbole |
| | - recommendation |
| | - benchmark |
| | --- |
| | |
| | # RecBole Model Checkpoints |
| |
|
| | This repository contains 52 model checkpoint(s) for RecBole. |
| |
|
| | ## Repository Information |
| |
|
| | - **Total Models**: 52 |
| | - **Format**: PyTorch `.pth` files |
| | - **Framework**: [RecBole](https://github.com/RUCAIBox/RecBole) |
| |
|
| | ## Available Models |
| |
|
| | ### BPR |
| |
|
| | - `model_BPR_seed_11_dataset_amazon_reviews_grocery_and_gourmet_food_retrain_checkpoint_idx_to_match_3_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_meat.pth` |
| | - `model_BPR_seed_11_dataset_amazon_reviews_grocery_and_gourmet_food_unlearning_algorithm_fanchuan_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_alcohol_unlearn_epoch_150_retrain_checkpoint_idx_to_match_1.pth` |
| | - `model_BPR_seed_11_dataset_amazon_reviews_grocery_and_gourmet_food_unlearning_algorithm_fanchuan_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_alcohol_unlearn_epoch_225_retrain_checkpoint_idx_to_match_2.pth` |
| | - `model_BPR_seed_11_dataset_amazon_reviews_grocery_and_gourmet_food_unlearning_algorithm_fanchuan_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_alcohol_unlearn_epoch_75_retrain_checkpoint_idx_to_match_0.pth` |
| | - `model_BPR_seed_11_dataset_amazon_reviews_grocery_and_gourmet_food_unlearning_algorithm_kookmin_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_alcohol_unlearn_epoch_150_retrain_checkpoint_idx_to_match_1.pth` |
| | - `model_BPR_seed_11_dataset_amazon_reviews_grocery_and_gourmet_food_unlearning_algorithm_kookmin_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_alcohol_unlearn_epoch_225_retrain_checkpoint_idx_to_match_2.pth` |
| | - `model_BPR_seed_11_dataset_amazon_reviews_grocery_and_gourmet_food_unlearning_algorithm_kookmin_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_alcohol_unlearn_epoch_75_retrain_checkpoint_idx_to_match_0.pth` |
| | - `model_BPR_seed_11_dataset_amazon_reviews_grocery_and_gourmet_food_unlearning_algorithm_scif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_alcohol_unlearn_epoch_150_retrain_checkpoint_idx_to_match_1.pth` |
| | - `model_BPR_seed_11_dataset_amazon_reviews_grocery_and_gourmet_food_unlearning_algorithm_scif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_alcohol_unlearn_epoch_225_retrain_checkpoint_idx_to_match_2.pth` |
| | - `model_BPR_seed_11_dataset_amazon_reviews_grocery_and_gourmet_food_unlearning_algorithm_scif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_alcohol_unlearn_epoch_75_retrain_checkpoint_idx_to_match_0.pth` |
| | - `model_BPR_seed_11_dataset_amazon_reviews_grocery_and_gourmet_food_unlearning_algorithm_seif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_alcohol_unlearn_epoch_150_retrain_checkpoint_idx_to_match_1.pth` |
| | - `model_BPR_seed_11_dataset_amazon_reviews_grocery_and_gourmet_food_unlearning_algorithm_seif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_alcohol_unlearn_epoch_225_retrain_checkpoint_idx_to_match_2.pth` |
| | - `model_BPR_seed_11_dataset_amazon_reviews_grocery_and_gourmet_food_unlearning_algorithm_seif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_alcohol_unlearn_epoch_75_retrain_checkpoint_idx_to_match_0.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_best.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_retrain_checkpoint_idx_to_match_3_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_fanchuan_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_1450_retrain_checkpoint_idx_to_match_0.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_fanchuan_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_2900_retrain_checkpoint_idx_to_match_1.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_fanchuan_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_4350_retrain_checkpoint_idx_to_match_2.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_fanchuan_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_5799_retrain_checkpoint_idx_to_match_3.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_kookmin_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_1450_retrain_checkpoint_idx_to_match_0.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_kookmin_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_2900_retrain_checkpoint_idx_to_match_1.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_kookmin_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_4350_retrain_checkpoint_idx_to_match_2.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_kookmin_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_5799_retrain_checkpoint_idx_to_match_3.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_scif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_1450_retrain_checkpoint_idx_to_match_0.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_scif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_2900_retrain_checkpoint_idx_to_match_1.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_scif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_4350_retrain_checkpoint_idx_to_match_2.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_scif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_5799_retrain_checkpoint_idx_to_match_3.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_seif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_1450_retrain_checkpoint_idx_to_match_0.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_seif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_2900_retrain_checkpoint_idx_to_match_1.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_seif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_4350_retrain_checkpoint_idx_to_match_2.pth` |
| | - `model_BPR_seed_11_dataset_goodreads_unlearning_algorithm_seif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_5799_retrain_checkpoint_idx_to_match_3.pth` |
| | - `model_BPR_seed_11_dataset_movielens_retrain_checkpoint_idx_to_match_3_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_violence.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_fanchuan_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_15_retrain_checkpoint_idx_to_match_0.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_fanchuan_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_30_retrain_checkpoint_idx_to_match_1.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_fanchuan_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_45_retrain_checkpoint_idx_to_match_2.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_kookmin_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_1462_retrain_checkpoint_idx_to_match_2.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_kookmin_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_15_retrain_checkpoint_idx_to_match_0.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_kookmin_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_30_retrain_checkpoint_idx_to_match_1.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_kookmin_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_45_retrain_checkpoint_idx_to_match_2.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_kookmin_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_487_retrain_checkpoint_idx_to_match_0.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_kookmin_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_60_retrain_checkpoint_idx_to_match_3.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_kookmin_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_975_retrain_checkpoint_idx_to_match_1.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_scif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_1462_retrain_checkpoint_idx_to_match_2.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_scif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_15_retrain_checkpoint_idx_to_match_0.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_scif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_30_retrain_checkpoint_idx_to_match_1.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_scif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_45_retrain_checkpoint_idx_to_match_2.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_scif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_487_retrain_checkpoint_idx_to_match_0.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_scif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_60_retrain_checkpoint_idx_to_match_3.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_scif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_975_retrain_checkpoint_idx_to_match_1.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_seif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_1462_retrain_checkpoint_idx_to_match_2.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_seif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_15_retrain_checkpoint_idx_to_match_0.pth` |
| | - `model_BPR_seed_11_dataset_movielens_unlearning_algorithm_seif_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health_unlearn_epoch_30_retrain_checkpoint_idx_to_match_1.pth` |
| |
|
| | ## Usage with RecBole |
| |
|
| | ### Method 1: Command Line |
| |
|
| | ```bash |
| | python run_recbole.py \ |
| | --model YOUR_MODEL \ |
| | --dataset YOUR_DATASET \ |
| | --eval_only \ |
| | --hf_model_path "hf://deem-data/recbole-models/FILENAME.pth" |
| | ``` |
| |
|
| | ### Method 2: Python API |
| |
|
| | ```python |
| | from recbole.utils import load_model_from_path |
| | import torch |
| | |
| | # Load checkpoint |
| | checkpoint = load_model_from_path( |
| | model_path="hf://deem-data/recbole-models/FILENAME.pth", |
| | map_location="cpu" |
| | ) |
| | |
| | # Load into your model |
| | model.load_state_dict(checkpoint["state_dict"]) |
| | ``` |
| |
|
| | ### Method 3: Download All Models |
| |
|
| | ```python |
| | from recbole.utils import HuggingFaceModelLoader |
| | |
| | loader = HuggingFaceModelLoader() |
| | repo_path = loader.download_repository( |
| | repo_id="deem-data/recbole-models", |
| | allow_patterns=["*.pth"] |
| | ) |
| | |
| | print(f"All models downloaded to: {repo_path}") |
| | ``` |
| |
|
| | ## Citation |
| |
|
| | If you use these models, please cite: |
| |
|
| | ```bibtex |
| | @inproceedings{recbole, |
| | title={RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms}, |
| | author={Wayne Xin Zhao and Shanlei Mu and Yupeng Hou and Zihan Lin and Yushuo Chen and Xingyu Pan and Kaiyuan Li and Yujie Lu and Hui Wang and Changxin Tian and Yingqian Min and Zhichao Feng and Xinyan Fan and Xu Chen and Pengfei Wang and Wendi Ji and Yaliang Li and Xiaoling Wang and Ji-Rong Wen}, |
| | booktitle={CIKM}, |
| | year={2021} |
| | } |
| | ``` |
| |
|
| | ## License |
| |
|
| | MIT License (or specify your own) |
| |
|
| | ## Contact |
| |
|
| | For questions about these models, please contact: [your email or GitHub] |
| |
|
