Update README.md

README.md

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 - pytorch_model_hub_mixin
 ---
 
-This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
-- Library: [More Information Needed]
-- Docs: [More Information Needed]
+# Model Card: MRI Brain Tumor Classification (EfficientNet-B1)
+
+## Model Details
+- **Model Name**: `MRIModel`
+- **Architecture**: EfficientNet-B1-based model for MRI brain tumor classification  
+- **Dataset**: [Brain Tumor MRI Dataset](https://www.kaggle.com/datasets/masoudnickparvar/brain-tumor-mri-dataset)  
+- **Batch Size**: 32  
+- **Loss Function**: CrossEntropy Loss  
+- **Optimizer**: Adam (learning rate = 1e-3)  
+- **Transfer Learning**: No (trained from scratch)  
+
+## Model Architecture
+This model is based on **EfficientNet-B1**, a lightweight yet powerful convolutional neural network, and has been adapted for **MRI-based brain tumor classification**.  
+
+### **Modifications**
+- **Input Channel Adaptation**: The first convolutional layer is modified to accept single-channel (grayscale) MRI scans.  
+- **Classifier Head**: The fully connected (FC) layer is modified to output 756 features.  
+
+## Implementation
+### **Model Definition**
+```python
+import torch
+import torch.nn as nn
+from torchvision.models import efficientnet_b1
+
+class MRIModel(nn.Module, PyTorchModelHubMixin):
+    def __init__(self):
+        super(MRIModel, self).__init__()
+        self.base_model = efficientnet_b1(weights=False)  # No pretrained weights
+        self.base_model.features[0] = nn.Sequential(
+            nn.Conv2d(1, 32, kernel_size=(3, 3), stride=(2, 2), bias=False),
+            nn.BatchNorm2d(
+                32, eps=0.001, momentum=0.1, affine=True, track_running_stats=True
+            ),
+            nn.ReLU6(inplace=True),
+        )
+        self.base_model.classifier = nn.Linear(1280, 756)
+
+    def forward(self, x):
+        x = self.base_model(x)
+        return x
+```
+
+This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration: