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+ ---
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+ license: mit
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+ tags:
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+ - recbole
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+ - recommendation
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+ - benchmark
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+ ---
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+
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+ # RecBole Model Checkpoints
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+
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+ This repository contains 52 model checkpoint(s) for RecBole.
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+
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+ ## Repository Information
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+
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+ - **Total Models**: 52
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+ - **Format**: PyTorch `.pth` files
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+ - **Framework**: [RecBole](https://github.com/RUCAIBox/RecBole)
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+
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+ ## Available Models
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+
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+ ### BPR
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+
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `model_BPR_seed_11_dataset_goodreads_best.pth`
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+ - `model_BPR_seed_11_dataset_goodreads_retrain_checkpoint_idx_to_match_3_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_health.pth`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `model_BPR_seed_11_dataset_movielens_retrain_checkpoint_idx_to_match_3_unlearning_fraction_0.0001_unlearning_sample_selection_method_sensitive_category_violence.pth`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+ - `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`
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+
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+ ## Usage with RecBole
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+
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+ ### Method 1: Command Line
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+
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+ ```bash
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+ python run_recbole.py \
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+ --model YOUR_MODEL \
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+ --dataset YOUR_DATASET \
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+ --eval_only \
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+ --hf_model_path "hf://deem-data/recbole-models/FILENAME.pth"
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+ ```
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+
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+ ### Method 2: Python API
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+
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+ ```python
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+ from recbole.utils import load_model_from_path
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+ import torch
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+
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+ # Load checkpoint
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+ checkpoint = load_model_from_path(
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+ model_path="hf://deem-data/recbole-models/FILENAME.pth",
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+ map_location="cpu"
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+ )
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+
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+ # Load into your model
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+ model.load_state_dict(checkpoint["state_dict"])
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+ ```
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+
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+ ### Method 3: Download All Models
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+
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+ ```python
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+ from recbole.utils import HuggingFaceModelLoader
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+
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+ loader = HuggingFaceModelLoader()
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+ repo_path = loader.download_repository(
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+ repo_id="deem-data/recbole-models",
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+ allow_patterns=["*.pth"]
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+ )
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+
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+ print(f"All models downloaded to: {repo_path}")
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+ ```
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+
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+ ## Citation
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+
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+ If you use these models, please cite:
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+
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+ ```bibtex
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+ @inproceedings{recbole,
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+ title={RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms},
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+ 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},
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+ booktitle={CIKM},
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+ year={2021}
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+ }
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+ ```
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+
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+ ## License
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+
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+ MIT License (or specify your own)
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+
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+ ## Contact
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+
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+ For questions about these models, please contact: [your email or GitHub]