Update README.md

README.md

@@ -1,3 +1,38 @@
----
-license: mit
----
+---
+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              | Model Size | Model Parameters | Recall@10 on Movies |
+|:-------------------------------|:--------:| :--------:|
+| [jibala-1022/easyrec-small](https://huggingface.co/jibala-1022/easyrec-roberta-small) | 243M | 121,364,313 | 0.0286 |
+| [jibala-1022/easyrec-base](https://huggingface.co/jibala-1022/easyrec-roberta-base)   | 328M | 163,891,545 | 0.0023 |
+
+## 🌟 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}
+}
+```