| | --- |
| | license: apache-2.0 |
| | language: en |
| | tags: |
| | - recommendation |
| | - collaborative filtering |
| | metrics: recall@10 |
| | base_model: FacebookAI/roberta-base |
| | pipeline_tag: sentence-similarity |
| | --- |
| | |
| | # EasyRec-Base |
| |
|
| | ## Overview |
| |
|
| | - **Description**: EasyRec is a series of language models designed for recommendations, trained to match the textual profiles of users and items with collaborative signals. |
| | - **Usage**: You can use EasyRec to encode user and item text embeddings based on the textual profiles that reflect their preferences for various recommendation scenarios. |
| | - **Evaluation**: We evaluate the performance of EasyRec in: (i) Text-based zero-shot recommendation and (ii) Text-enhanced collaborative filtering. |
| | - **Finetuned from model:** EasyRec is finetuned from [RoBERTa](https://huggingface.co/FacebookAI/roberta-large) within English. |
| |
|
| | For details please refer [💻[GitHub Code](https://github.com/jibala-1022/EasyRec)] and [📖[Paper](https://arxiv.org/abs/2408.08821)]. |
| |
|
| | ### Model List |
| | We release a series of EasyRec checkpoints with varying sizes. You can easily load these models from Hugging Face by replacing the model name. |
| | | Model | Size | Parameters | Recall@10 on Movies | |
| | |:-----:|:----:|:----------:|:-------------------:| |
| | | [jibala-1022/easyrec-small](https://huggingface.co/jibala-1022/easyrec-small) | 243 MB | 121,364,313 | 0.0086 | |
| | | [jibala-1022/easyrec-base](https://huggingface.co/jibala-1022/easyrec-base) | 328 MB | 163,891,545 | 0.0166 | |
| | | [jibala-1022/easyrec-large](https://huggingface.co/jibala-1022/easyrec-large) | 816 MB | 407,933,017 | 0.0166 | |
| |
|
| | ## 🌟 Citation |
| | ```bibtex |
| | @article{ren2024easyrec, |
| | title={EasyRec: Simple yet Effective Language Models for Recommendation}, |
| | author={Ren, Xubin and Huang, Chao}, |
| | journal={arXiv preprint arXiv:2408.08821}, |
| | year={2024} |
| | } |
| | ``` |
