removed model

Readme.md

@@ -1,48 +0,0 @@
-# ResNet50 Model Implementation
-
-This implementation provides a customizable ResNet50 model for image classification tasks.
-
-## Model Architecture
-
-The model uses the ResNet50 architecture, which is a deep convolutional neural network with 50 layers. Key features include:
-
-- Based on the standard ResNet50 architecture
-- Customizable number of output classes
-- Modified final fully connected layer to match the desired number of classes
-- Initialized from scratch (no pre-training)
-
-## Functions
-
-### `get_model(num_classes)`
-Initializes a new ResNet50 model with a custom number of output classes.
-- **Input**: Number of classes (integer)
-- **Output**: Initialized ResNet50 model
-- **Note**: The model is initialized without pre-trained weights
-
-### `save_model(model, path)`
-Saves the model's state dictionary to a specified path.
-- **Input**: 
-  - model: Trained PyTorch model
-  - path: File path for saving the model
-
-### `load_model(num_classes, path)`
-Loads a previously saved model.
-- **Input**:
-  - num_classes: Number of output classes
-  - path: Path to the saved model file
-- **Output**: Loaded ResNet50 model
-
-## Usage Example
-
-```python
-model = get_model(num_classes=1000)
-save_model(model, 'model.pth')
-loaded_model = load_model(num_classes=1000, path='model.pth')
-```
-
-## Attachments 
-![Trained on AWS](https://github.com/srtangirala/resnet-training/blob/main/logs/images/aws.png)
-![Logs 1](https://github.com/srtangirala/resnet-training/blob/main/logs/images/logs-1.png)
-![Logs 2](https://github.com/srtangirala/resnet-training/blob/main/logs/images/logs-2.png)
-
-