Add pipeline tag and library name

README.md

@@ -1,3 +1,55 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+pipeline_tag: any-to-any
+library_name: fuxictr
+---
+
+## Official implementation code of DISCO.AHU team
+## 🔥 Winning 2nd Place in WWW2025 Multimodal CTR Prediction Challenge Track
+
+### 🔥 Follow to perfectly reproduce the results of this code.
+
+- To facilitate reproducibility, we share the model checkpoints on Hugging Face: https://huggingface.co/salmon1802/QIN/tree/main
+- In ./checkpoints and ./submission folders have our run logs and submission files, respectively.
+- This submission can be reproduced manually by following the actions below, or by directly using the one-click run script run.sh
+
+### Data Preparation
+
+1. Download the datasets at: https://recsys.westlake.edu.cn/MicroLens_1M_MMCTR
+
+2. Unzip the data files to the `data` directory
+
+    ```bash
+   cd ./data/
+   wget -r -np -nH --cut-dirs=1 http://recsys.westlake.edu.cn/MicroLens_1M_MMCTR/MicroLens_1M_x1/
+    ```
+
+### Environment
+
+We run the experiments on RTX 4090 GPU of AutoDL.com
+
+Please set up the environment as follows. 
+
++ torch==2.0.0+cu118
++ fuxictr==2.3.7
+
+```
+conda create -n fuxictr_www python==3.8
+pip install torch==2.0.0 torchvision==0.15.1 torchaudio==2.0.1 --index-url https://download.pytorch.org/whl/cu118
+pip install -r requirements.txt
+source activate fuxictr_www
+```
+
+### How to Run
+
+ Train the model on train and validation sets:
+
+    ```
+    python run_expid.py
+    ```
+The parameters QIN_variety_v9 in __./config/qin_config/model_config.yaml__ are set to the optimal hyperparameters in the environment described above.
+
+#### Tips
+It is worth mentioning that after our tests, we find that although the parameter num_row = 4 achieves the best performance in the above environments, there is training instability in some environments.
+
+When this happens, we suggest that sacrificing some performance in favor of setting num_row = 3 reproduces the results well.