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@@ -282,10 +282,13 @@ In addition, the trainer is responsible for the following:
 #### Integration with Freqai module 
 Like all freqai models, PyTorch models inherit `IFreqaiModel`. `IFreqaiModel` declares three abstract methods: `train`, `fit`, and `predict`. we implement these methods in three levels of hierarchy.
 From top to bottom:
-1. `BasePyTorchModel` - all `BasePyTorch*` inherit it. Implements the `train` method responsible for general data preparation (e.g., data normalization) and calling the `fit` method. Sets `device _type` attribute used by children classes. Sets `model_type` attribute used by the parent class.
-2. `BasePyTorch*` - Here, the `*` represents a group of algorithms, such as classifiers or regressors. the `predict` method is responsible for data preprocessing, predicting, and postprocessing if needed.
 
-3. PyTorch*Classifier / PyTorch*Regressor - implements the `fit` method, responsible for the main train flaw, where we initialize the trainer and model objects.
+![image](assets/freqai_pytorch-diagram.png)
+
+1. `BasePyTorchModel` - Implements the `train` method. all `BasePyTorch*` inherit it. responsible for general data preparation (e.g., data normalization) and calling the `fit` method. Sets `device _type` attribute used by children classes. Sets `model_type` attribute used by the parent class.
+2. `BasePyTorch*` -  Implements the `predict` method. Here, the `*` represents a group of algorithms, such as classifiers or regressors. responsible for data preprocessing, predicting, and postprocessing if needed.
+
+3. `PyTorch*Classifier` / `PyTorch*Regressor` - implements the `fit` method. responsible for the main train flaw, where we initialize the trainer and model objects.
 
 #### Full example
 Building a PyTorch regressor using MLP (multilayer perceptron) model, MSELoss criterion, and AdamW optimizer.