update readme

README.md

@@ -21,7 +21,7 @@
 #稳定版 
 pip install torch-rechub
 
-#最新版
+#最新版（推荐）
 1. git clone https://github.com/datawhalechina/torch-rechub.git
 2. cd torch-rechub
 3. python setup.py install
@@ -79,23 +79,27 @@ pip install torch-rechub
 
 ## 快速使用
 
-### 单任务排序
+### 使用案例
+
+- 所有模型使用案例参考 `/examples`
+
+- 202206 Datawhale-RecHub推荐课程 组队学习期间notebook教程参考 `/tutorials`
+
+### 精排（CTR预测）
 
 ```python
-from torch_rechub.models.ranking import WideDeep, DeepFM, DIN
+from torch_rechub.models.ranking import DeepFM
 from torch_rechub.trainers import CTRTrainer
-from torch_rechub.basic.utils import DataGenerator
+from torch_rechub.utils.data import DataGenerator
 
 dg = DataGenerator(x, y)
-train_dataloader, val_dataloader, test_dataloader = dg.generate_dataloader()
+train_dataloader, val_dataloader, test_dataloader = dg.generate_dataloader(split_ratio=[0.7, 0.1], batch_size=256)
 
 model = DeepFM(deep_features=deep_features, fm_features=fm_features, mlp_params={"dims": [256, 128], "dropout": 0.2, "activation": "relu"})
 
 ctr_trainer = CTRTrainer(model)
 ctr_trainer.fit(train_dataloader, val_dataloader)
 auc = ctr_trainer.evaluate(ctr_trainer.model, test_dataloader)
-
-
 ```
 
 ### 多任务排序
@@ -104,9 +108,36 @@ auc = ctr_trainer.evaluate(ctr_trainer.model, test_dataloader)
 from torch_rechub.models.multi_task import SharedBottom, ESMM, MMOE, PLE, AITM
 from torch_rechub.trainers import MTLTrainer
 
-model = MMOE(features, task_types, n_expert=3, expert_params={"dims": [64,32,16]}, tower_params_list=[{"dims": [8]}, {"dims": [8]}])
+task_types = ["classification", "classification"] 
+model = MMOE(features, task_types, 8, expert_params={"dims": [32,16]}, tower_params_list=[{"dims": [32, 16]}, {"dims": [32, 16]}])
 
-ctr_trainer = MTLTrainer(model)
-ctr_trainer.fit(train_dataloader, val_dataloader)
+mtl_trainer = MTLTrainer(model)
+mtl_trainer.fit(train_dataloader, val_dataloader)
 auc = ctr_trainer.evaluate(ctr_trainer.model, test_dataloader)
 ```
+
+### 召回模型
+
+```python
+from torch_rechub.models.matching import DSSM
+from torch_rechub.trainers import MatchTrainer
+from torch_rechub.utils.data import MatchDataGenerator
+
+dg = MatchDataGenerator(x y)
+train_dl, test_dl, item_dl = dg.generate_dataloader(test_user, all_item, batch_size=256)
+
+model = DSSM(user_features, item_features, temperature=0.02,
+             user_params={
+                 "dims": [256, 128, 64],
+                 "activation": 'prelu',  
+             },
+             item_params={
+                 "dims": [256, 128, 64],
+                 "activation": 'prelu', 
+             })
+
+match_trainer = MatchTrainer(model)
+match_trainer.fit(train_dl)
+
+```
+